{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Fully-Connected Neural Nets\n",
    "In the previous homework you implemented a fully-connected two-layer neural network on CIFAR-10. The implementation was simple but not very modular since the loss and gradient were computed in a single monolithic function. This is manageable for a simple two-layer network, but would become impractical as we move to bigger models. Ideally we want to build networks using a more modular design so that we can implement different layer types in isolation and then snap them together into models with different architectures.\n",
    "\n",
    "In this exercise we will implement fully-connected networks using a more modular approach. For each layer we will implement a `forward` and a `backward` function. The `forward` function will receive inputs, weights, and other parameters and will return both an output and a `cache` object storing data needed for the backward pass, like this:\n",
    "\n",
    "```python\n",
    "def layer_forward(x, w):\n",
    "  \"\"\" Receive inputs x and weights w \"\"\"\n",
    "  # Do some computations ...\n",
    "  z = # ... some intermediate value\n",
    "  # Do some more computations ...\n",
    "  out = # the output\n",
    "   \n",
    "  cache = (x, w, z, out) # Values we need to compute gradients\n",
    "   \n",
    "  return out, cache\n",
    "```\n",
    "\n",
    "The backward pass will receive upstream derivatives and the `cache` object, and will return gradients with respect to the inputs and weights, like this:\n",
    "\n",
    "```python\n",
    "def layer_backward(dout, cache):\n",
    "  \"\"\"\n",
    "  Receive derivative of loss with respect to outputs and cache,\n",
    "  and compute derivative with respect to inputs.\n",
    "  \"\"\"\n",
    "  # Unpack cache values\n",
    "  x, w, z, out = cache\n",
    "  \n",
    "  # Use values in cache to compute derivatives\n",
    "  dx = # Derivative of loss with respect to x\n",
    "  dw = # Derivative of loss with respect to w\n",
    "  \n",
    "  return dx, dw\n",
    "```\n",
    "\n",
    "After implementing a bunch of layers this way, we will be able to easily combine them to build classifiers with different architectures.\n",
    "\n",
    "In addition to implementing fully-connected networks of arbitrary depth, we will also explore different update rules for optimization, and introduce Dropout as a regularizer and Batch Normalization as a tool to more efficiently optimize deep networks.\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "run the following from the cs231n directory and try again:\n",
      "python setup.py build_ext --inplace\n",
      "You may also need to restart your iPython kernel\n"
     ]
    }
   ],
   "source": [
    "# As usual, a bit of setup\n",
    "from __future__ import print_function\n",
    "import time\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from cs231n.classifiers.fc_net import *\n",
    "from cs231n.data_utils import get_CIFAR10_data\n",
    "from cs231n.gradient_check import eval_numerical_gradient, eval_numerical_gradient_array\n",
    "from cs231n.solver import Solver\n",
    "\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10.0, 8.0) # set default size of plots\n",
    "plt.rcParams['image.interpolation'] = 'nearest'\n",
    "plt.rcParams['image.cmap'] = 'gray'\n",
    "\n",
    "# for auto-reloading external modules\n",
    "# see http://stackoverflow.com/questions/1907993/autoreload-of-modules-in-ipython\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "def rel_error(x, y):\n",
    "  \"\"\" returns relative error \"\"\"\n",
    "  return np.max(np.abs(x - y) / (np.maximum(1e-8, np.abs(x) + np.abs(y))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('X_train: ', (49000, 3, 32, 32))\n",
      "('X_test: ', (1000, 3, 32, 32))\n",
      "('X_val: ', (1000, 3, 32, 32))\n",
      "('y_train: ', (49000,))\n",
      "('y_test: ', (1000,))\n",
      "('y_val: ', (1000,))\n"
     ]
    }
   ],
   "source": [
    "# Load the (preprocessed) CIFAR10 data.\n",
    "\n",
    "data = get_CIFAR10_data()\n",
    "for k, v in list(data.items()):\n",
    "  print(('%s: ' % k, v.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Affine layer: foward\n",
    "Open the file `cs231n/layers.py` and implement the `affine_forward` function.\n",
    "\n",
    "Once you are done you can test your implementaion by running the following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing affine_forward function:\n",
      "difference:  9.76984772881e-10\n"
     ]
    }
   ],
   "source": [
    "# Test the affine_forward function\n",
    "\n",
    "num_inputs = 2\n",
    "input_shape = (4, 5, 6)\n",
    "output_dim = 3\n",
    "\n",
    "input_size = num_inputs * np.prod(input_shape)\n",
    "weight_size = output_dim * np.prod(input_shape)\n",
    "\n",
    "x = np.linspace(-0.1, 0.5, num=input_size).reshape(num_inputs, *input_shape)\n",
    "w = np.linspace(-0.2, 0.3, num=weight_size).reshape(np.prod(input_shape), output_dim)\n",
    "b = np.linspace(-0.3, 0.1, num=output_dim)\n",
    "\n",
    "out, _ = affine_forward(x, w, b)\n",
    "correct_out = np.array([[ 1.49834967,  1.70660132,  1.91485297],\n",
    "                        [ 3.25553199,  3.5141327,   3.77273342]])\n",
    "\n",
    "# Compare your output with ours. The error should be around 1e-9.\n",
    "print('Testing affine_forward function:')\n",
    "print('difference: ', rel_error(out, correct_out))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Affine layer: backward\n",
    "Now implement the `affine_backward` function and test your implementation using numeric gradient checking."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing affine_backward function:\n",
      "dx error:  1.09081995087e-10\n",
      "dw error:  2.17526355046e-10\n",
      "db error:  7.73697883449e-12\n"
     ]
    }
   ],
   "source": [
    "# Test the affine_backward function\n",
    "np.random.seed(231)\n",
    "x = np.random.randn(10, 2, 3)\n",
    "w = np.random.randn(6, 5)\n",
    "b = np.random.randn(5)\n",
    "dout = np.random.randn(10, 5)\n",
    "\n",
    "dx_num = eval_numerical_gradient_array(lambda x: affine_forward(x, w, b)[0], x, dout)\n",
    "dw_num = eval_numerical_gradient_array(lambda w: affine_forward(x, w, b)[0], w, dout)\n",
    "db_num = eval_numerical_gradient_array(lambda b: affine_forward(x, w, b)[0], b, dout)\n",
    "\n",
    "_, cache = affine_forward(x, w, b)\n",
    "dx, dw, db = affine_backward(dout, cache)\n",
    "\n",
    "# The error should be around 1e-10\n",
    "print('Testing affine_backward function:')\n",
    "print('dx error: ', rel_error(dx_num, dx))\n",
    "print('dw error: ', rel_error(dw_num, dw))\n",
    "print('db error: ', rel_error(db_num, db))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# ReLU layer: forward\n",
    "Implement the forward pass for the ReLU activation function in the `relu_forward` function and test your implementation using the following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing relu_forward function:\n",
      "difference:  4.99999979802e-08\n"
     ]
    }
   ],
   "source": [
    "# Test the relu_forward function\n",
    "\n",
    "x = np.linspace(-0.5, 0.5, num=12).reshape(3, 4)\n",
    "\n",
    "out, _ = relu_forward(x)\n",
    "correct_out = np.array([[ 0.,          0.,          0.,          0.,        ],\n",
    "                        [ 0.,          0.,          0.04545455,  0.13636364,],\n",
    "                        [ 0.22727273,  0.31818182,  0.40909091,  0.5,       ]])\n",
    "\n",
    "# Compare your output with ours. The error should be around 5e-8\n",
    "print('Testing relu_forward function:')\n",
    "print('difference: ', rel_error(out, correct_out))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# ReLU layer: backward\n",
    "Now implement the backward pass for the ReLU activation function in the `relu_backward` function and test your implementation using numeric gradient checking:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing relu_backward function:\n",
      "dx error:  3.27563491363e-12\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(231)\n",
    "x = np.random.randn(10, 10)\n",
    "dout = np.random.randn(*x.shape)\n",
    "\n",
    "dx_num = eval_numerical_gradient_array(lambda x: relu_forward(x)[0], x, dout)\n",
    "\n",
    "_, cache = relu_forward(x)\n",
    "dx = relu_backward(dout, cache)\n",
    "\n",
    "# The error should be around 3e-12\n",
    "print('Testing relu_backward function:')\n",
    "print('dx error: ', rel_error(dx_num, dx))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# \"Sandwich\" layers\n",
    "There are some common patterns of layers that are frequently used in neural nets. For example, affine layers are frequently followed by a ReLU nonlinearity. To make these common patterns easy, we define several convenience layers in the file `cs231n/layer_utils.py`.\n",
    "\n",
    "For now take a look at the `affine_relu_forward` and `affine_relu_backward` functions, and run the following to numerically gradient check the backward pass:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing affine_relu_forward:\n",
      "dx error:  6.39553504205e-11\n",
      "dw error:  8.16201110576e-11\n",
      "db error:  7.82672402146e-12\n"
     ]
    }
   ],
   "source": [
    "from cs231n.layer_utils import affine_relu_forward, affine_relu_backward\n",
    "np.random.seed(231)\n",
    "x = np.random.randn(2, 3, 4)\n",
    "w = np.random.randn(12, 10)\n",
    "b = np.random.randn(10)\n",
    "dout = np.random.randn(2, 10)\n",
    "\n",
    "out, cache = affine_relu_forward(x, w, b)\n",
    "dx, dw, db = affine_relu_backward(dout, cache)\n",
    "\n",
    "dx_num = eval_numerical_gradient_array(lambda x: affine_relu_forward(x, w, b)[0], x, dout)\n",
    "dw_num = eval_numerical_gradient_array(lambda w: affine_relu_forward(x, w, b)[0], w, dout)\n",
    "db_num = eval_numerical_gradient_array(lambda b: affine_relu_forward(x, w, b)[0], b, dout)\n",
    "\n",
    "print('Testing affine_relu_forward:')\n",
    "print('dx error: ', rel_error(dx_num, dx))\n",
    "print('dw error: ', rel_error(dw_num, dw))\n",
    "print('db error: ', rel_error(db_num, db))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Loss layers: Softmax and SVM\n",
    "You implemented these loss functions in the last assignment, so we'll give them to you for free here. You should still make sure you understand how they work by looking at the implementations in `cs231n/layers.py`.\n",
    "\n",
    "You can make sure that the implementations are correct by running the following:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing svm_loss:\n",
      "loss:  8.9996027491\n",
      "dx error:  1.40215660067e-09\n",
      "\n",
      "Testing softmax_loss:\n",
      "loss:  2.3025458445\n",
      "dx error:  9.38467316199e-09\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(231)\n",
    "num_classes, num_inputs = 10, 50\n",
    "x = 0.001 * np.random.randn(num_inputs, num_classes)\n",
    "y = np.random.randint(num_classes, size=num_inputs)\n",
    "\n",
    "dx_num = eval_numerical_gradient(lambda x: svm_loss(x, y)[0], x, verbose=False)\n",
    "loss, dx = svm_loss(x, y)\n",
    "\n",
    "# Test svm_loss function. Loss should be around 9 and dx error should be 1e-9\n",
    "print('Testing svm_loss:')\n",
    "print('loss: ', loss)\n",
    "print('dx error: ', rel_error(dx_num, dx))\n",
    "\n",
    "dx_num = eval_numerical_gradient(lambda x: softmax_loss(x, y)[0], x, verbose=False)\n",
    "loss, dx = softmax_loss(x, y)\n",
    "\n",
    "# Test softmax_loss function. Loss should be 2.3 and dx error should be 1e-8\n",
    "print('\\nTesting softmax_loss:')\n",
    "print('loss: ', loss)\n",
    "print('dx error: ', rel_error(dx_num, dx))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Two-layer network\n",
    "In the previous assignment you implemented a two-layer neural network in a single monolithic class. Now that you have implemented modular versions of the necessary layers, you will reimplement the two layer network using these modular implementations.\n",
    "\n",
    "Open the file `cs231n/classifiers/fc_net.py` and complete the implementation of the `TwoLayerNet` class. This class will serve as a model for the other networks you will implement in this assignment, so read through it to make sure you understand the API. You can run the cell below to test your implementation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing initialization ... \n",
      "Testing test-time forward pass ... \n",
      "Testing training loss (no regularization)\n",
      "Running numeric gradient check with reg =  0.0\n",
      "W1 relative error: 1.22e-08\n",
      "W2 relative error: 3.50e-10\n",
      "b1 relative error: 8.37e-09\n",
      "b2 relative error: 2.53e-10\n",
      "Running numeric gradient check with reg =  0.7\n",
      "W1 relative error: 2.53e-07\n",
      "W2 relative error: 7.98e-08\n",
      "b1 relative error: 1.56e-08\n",
      "b2 relative error: 9.09e-10\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(231)\n",
    "N, D, H, C = 3, 5, 50, 7\n",
    "X = np.random.randn(N, D)\n",
    "y = np.random.randint(C, size=N)\n",
    "\n",
    "std = 1e-3\n",
    "model = TwoLayerNet(input_dim=D, hidden_dim=H, num_classes=C, weight_scale=std)\n",
    "\n",
    "print('Testing initialization ... ')\n",
    "W1_std = abs(model.params['W1'].std() - std)\n",
    "b1 = model.params['b1']\n",
    "W2_std = abs(model.params['W2'].std() - std)\n",
    "b2 = model.params['b2']\n",
    "assert W1_std < std / 10, 'First layer weights do not seem right'\n",
    "assert np.all(b1 == 0), 'First layer biases do not seem right'\n",
    "assert W2_std < std / 10, 'Second layer weights do not seem right'\n",
    "assert np.all(b2 == 0), 'Second layer biases do not seem right'\n",
    "\n",
    "print('Testing test-time forward pass ... ')\n",
    "model.params['W1'] = np.linspace(-0.7, 0.3, num=D*H).reshape(D, H)\n",
    "model.params['b1'] = np.linspace(-0.1, 0.9, num=H)\n",
    "model.params['W2'] = np.linspace(-0.3, 0.4, num=H*C).reshape(H, C)\n",
    "model.params['b2'] = np.linspace(-0.9, 0.1, num=C)\n",
    "X = np.linspace(-5.5, 4.5, num=N*D).reshape(D, N).T\n",
    "scores = model.loss(X)\n",
    "correct_scores = np.asarray(\n",
    "  [[11.53165108,  12.2917344,   13.05181771,  13.81190102,  14.57198434, 15.33206765,  16.09215096],\n",
    "   [12.05769098,  12.74614105,  13.43459113,  14.1230412,   14.81149128, 15.49994135,  16.18839143],\n",
    "   [12.58373087,  13.20054771,  13.81736455,  14.43418138,  15.05099822, 15.66781506,  16.2846319 ]])\n",
    "scores_diff = np.abs(scores - correct_scores).sum()\n",
    "assert scores_diff < 1e-6, 'Problem with test-time forward pass'\n",
    "\n",
    "print('Testing training loss (no regularization)')\n",
    "y = np.asarray([0, 5, 1])\n",
    "loss, grads = model.loss(X, y)\n",
    "correct_loss = 3.4702243556\n",
    "assert abs(loss - correct_loss) < 1e-10, 'Problem with training-time loss'\n",
    "\n",
    "model.reg = 1.0\n",
    "loss, grads = model.loss(X, y)\n",
    "correct_loss = 26.5948426952\n",
    "assert abs(loss - correct_loss) < 1e-10, 'Problem with regularization loss'\n",
    "\n",
    "for reg in [0.0, 0.7]:\n",
    "  print('Running numeric gradient check with reg = ', reg)\n",
    "  model.reg = reg\n",
    "  loss, grads = model.loss(X, y)\n",
    "\n",
    "  for name in sorted(grads):\n",
    "    f = lambda _: model.loss(X, y)[0]\n",
    "    grad_num = eval_numerical_gradient(f, model.params[name], verbose=False)\n",
    "    print('%s relative error: %.2e' % (name, rel_error(grad_num, grads[name])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Solver\n",
    "In the previous assignment, the logic for training models was coupled to the models themselves. Following a more modular design, for this assignment we have split the logic for training models into a separate class.\n",
    "\n",
    "Open the file `cs231n/solver.py` and read through it to familiarize yourself with the API. After doing so, use a `Solver` instance to train a `TwoLayerNet` that achieves at least `50%` accuracy on the validation set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(Iteration 1 / 4900) loss: 2.301434\n",
      "(Epoch 0 / 10) train acc: 0.164000; val_acc: 0.134000\n",
      "(Iteration 101 / 4900) loss: 1.824051\n",
      "(Iteration 201 / 4900) loss: 1.961900\n",
      "(Iteration 301 / 4900) loss: 1.613144\n",
      "(Iteration 401 / 4900) loss: 1.495818\n",
      "(Epoch 1 / 10) train acc: 0.450000; val_acc: 0.451000\n",
      "(Iteration 501 / 4900) loss: 1.563394\n",
      "(Iteration 601 / 4900) loss: 1.443666\n",
      "(Iteration 701 / 4900) loss: 1.604075\n",
      "(Iteration 801 / 4900) loss: 1.605911\n",
      "(Iteration 901 / 4900) loss: 1.408392\n",
      "(Epoch 2 / 10) train acc: 0.480000; val_acc: 0.464000\n",
      "(Iteration 1001 / 4900) loss: 1.455671\n",
      "(Iteration 1101 / 4900) loss: 1.468152\n",
      "(Iteration 1201 / 4900) loss: 1.380462\n",
      "(Iteration 1301 / 4900) loss: 1.280830\n",
      "(Iteration 1401 / 4900) loss: 1.445764\n",
      "(Epoch 3 / 10) train acc: 0.503000; val_acc: 0.479000\n",
      "(Iteration 1501 / 4900) loss: 1.384686\n",
      "(Iteration 1601 / 4900) loss: 1.332996\n",
      "(Iteration 1701 / 4900) loss: 1.341420\n",
      "(Iteration 1801 / 4900) loss: 1.456930\n",
      "(Iteration 1901 / 4900) loss: 1.427660\n",
      "(Epoch 4 / 10) train acc: 0.504000; val_acc: 0.487000\n",
      "(Iteration 2001 / 4900) loss: 1.425840\n",
      "(Iteration 2101 / 4900) loss: 1.389251\n",
      "(Iteration 2201 / 4900) loss: 1.458540\n",
      "(Iteration 2301 / 4900) loss: 1.190365\n",
      "(Iteration 2401 / 4900) loss: 1.231720\n",
      "(Epoch 5 / 10) train acc: 0.529000; val_acc: 0.481000\n",
      "(Iteration 2501 / 4900) loss: 1.311956\n",
      "(Iteration 2601 / 4900) loss: 1.257376\n",
      "(Iteration 2701 / 4900) loss: 1.255261\n",
      "(Iteration 2801 / 4900) loss: 1.359596\n",
      "(Iteration 2901 / 4900) loss: 1.252704\n",
      "(Epoch 6 / 10) train acc: 0.563000; val_acc: 0.512000\n",
      "(Iteration 3001 / 4900) loss: 1.141624\n",
      "(Iteration 3101 / 4900) loss: 1.041271\n",
      "(Iteration 3201 / 4900) loss: 1.537659\n",
      "(Iteration 3301 / 4900) loss: 1.195672\n",
      "(Iteration 3401 / 4900) loss: 1.411472\n",
      "(Epoch 7 / 10) train acc: 0.547000; val_acc: 0.494000\n",
      "(Iteration 3501 / 4900) loss: 1.193842\n",
      "(Iteration 3601 / 4900) loss: 1.033797\n",
      "(Iteration 3701 / 4900) loss: 1.246135\n",
      "(Iteration 3801 / 4900) loss: 1.203015\n",
      "(Iteration 3901 / 4900) loss: 0.929300\n",
      "(Epoch 8 / 10) train acc: 0.545000; val_acc: 0.502000\n",
      "(Iteration 4001 / 4900) loss: 1.089804\n",
      "(Iteration 4101 / 4900) loss: 1.174137\n",
      "(Iteration 4201 / 4900) loss: 1.052676\n",
      "(Iteration 4301 / 4900) loss: 0.998013\n",
      "(Iteration 4401 / 4900) loss: 1.530019\n",
      "(Epoch 9 / 10) train acc: 0.594000; val_acc: 0.513000\n",
      "(Iteration 4501 / 4900) loss: 1.118980\n",
      "(Iteration 4601 / 4900) loss: 1.280910\n",
      "(Iteration 4701 / 4900) loss: 1.336721\n",
      "(Iteration 4801 / 4900) loss: 1.083075\n",
      "(Epoch 10 / 10) train acc: 0.583000; val_acc: 0.476000\n"
     ]
    }
   ],
   "source": [
    "model = TwoLayerNet()\n",
    "solver = None\n",
    "\n",
    "##############################################################################\n",
    "# TODO: Use a Solver instance to train a TwoLayerNet that achieves at least  #\n",
    "# 50% accuracy on the validation set.                                        #\n",
    "##############################################################################\n",
    "solver = Solver(model, data,\n",
    "                update_rule='sgd',\n",
    "                optim_config={\n",
    "                    'learning_rate': 1e-3,\n",
    "                },\n",
    "                lr_decay=0.95,\n",
    "                num_epochs=10, batch_size=100,\n",
    "                print_every=100)\n",
    "solver.train()\n",
    "##############################################################################\n",
    "#                             END OF YOUR CODE                               #\n",
    "##############################################################################"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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8sOSams6f+D5gKPAV4GKg2KMsUChMY8eOBSxZsqo7H0GSJEmSJEnqUHcryy4DaoAfALtL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4IsI93s9PT0TFzd8BjrGf3ri9QEw65FuZBfOjiyn/xL0DfJNJGU57ki7el0zh1MfKDs9BOd8rWN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Wj0lwWeZumFIjtWsXLFlScWps27b4ud6946XYTTfFi7Gzz4b09GjzJoNj3jGyrKT8nvSU\n9PLHH7u37c6gkwZVKsK6ZHYhLSV5/+fUokySJElSY5P3kzxevvhlVoQrKMuovN5yQ0ren+6kJqS0\nFFasqFiMLV8enyZr3x6GDIExY+IF2ZAh8YX5VVF1O0Ye+WhkTTtGntbhNL5wyhcqFWGd2nQiJUiJ\n8DuTJEmSpOYnKyuLhS8s5Me/+DG/W/A7NrIxYZ/tY5hSBLZsOfwoZX4+LF4MhYWQkhKfEjtyrbHe\nvePHG5NEP7a3t2Rv5d0ij7JjZFaLrBofizzajpGSJEmSpMahoKCAnJwc8DFMqWnYvx/efLPi1Niq\nVfFzXbrA0KFwxx3xxykHDYLMzGjzVqewsJA7/vsOnn7paUpSS0gvTWf4sOHk/STvuBaEP94dIwed\nNIgrzryi0kL5x7tjpCRJkiSpebIsk+pRGMZ3ozyyGCsogOJiaNECcnLgsssOT42dcgokw2BTYWEh\nQy8eyorTV1B2WVl8N5IQpq2axssXv8zCFxZWKsyq2jHy07tFHm3HyPNPPb/SrpGJ3DFSkiRJktT8\nWJZJx2HPHnjjjcPFWH4+bDz4GHV2drwQGzEi/vWzn4WWjXMzxKO647/viBdlpx+xqGIAZb3KWBGu\nYPjY4Qy9fmitdoy8uNfFlR6L7JbVjRapLSL4DiVJkiRJirMsk45RWRm8/37FqbG3344vzp+ZGV94\n/6ab4sVYbi507hx14trbV7KPzXs2s2n3JjYWbmTT7k1s2r2JhxY8RNmIqncfKetVxl8e+QsfD/i4\nSe8YKUmSJElqHvzJVarG9u3xhfePnBrbsSP+2GTfvvFS7NAOlX37Qmpq1ImrVhaWsW3vtvLi68gS\nbNOeisd2Fu+scG9qkErnNp0pTimOP3pZlQBOPuFkVo1b5WL5kiRJkqSkZ1kmAQcOxKfEjizGVq6M\nnzvxxHghdttt8a+DB0O7dtHmBdi9f/fh0quGEmzLni2UhqUV7m3fqj1dM7tyUuZJnJR5EgO6DqBr\nZtfyY4d+f2LGiaQEKWQ/ms3qcHXVhVkI6aXpFmWSJEmSpCbBskzN0oYN8ULsUDn2xhuwdy+kpcE5\n58BFF8FPfhIvx047LXGL8B8oO8CWPVsqlGDlRdieisd2799d4d4WqS0qFF6Duw0uf31kCdYlswut\n0lrVKtfwYcOZtmoaZb0qP4qZ8mEKl1102XF935IkSZIkNRaWZWryioriO1IeudbY2rXxcz16xAux\nn/88/nXgQGjdun4/PwxDdhXvYuPujZVLsE8d27pnKyFhhfs7ZnQsL7yy22cztPvQKkuw9q3aN9h0\nV95P8nj54pdZEa6IF2YHd8NM+TCFPh/04RfTf9EgnytJkiRJUqJZlqlJCUNYtari45TLlkFJSbwE\nGzTo8O6Uublw8sl1/6z9pfvZvHtzlaXXp18fuSskQOu01pyUdfhxx/N6nFfh9aFfXdp0IT01/Tj/\nVI5fVlYWC19YyI9/8WMWPL2AkpQS0svSuWzYZfxi+i/IysqKOqIkSZIkSfUiCMPw6FclWBAEA4Gl\nS5cuZeDAgVHHUSO2a1d8Ef4jH6ncti1+rnfveCl26Fe/fpB+lN4pDEO279tebel15LHt+7ZXuDcl\nSKFzm84VC682XasswbJaZCX1Gl9hGCZ1fkmSJElS8igoKCAnJwcgJwzDgob+PCfLlBD1Ua6UlsKK\nFRUfp1y+PD5N1r59fFLsllvixdiQIXDCCYfv3Veyj3U1TH4dOrZ592ZKykoqfG5Wi6wKhddnOn0m\n/vjjp0qwThmdSE1ppFti1jOLMkmSJElSU2VZpgZTWFjIHf99B0+/9DQlqSWkl6YzfNhw8n6Sd0yP\n7W3ZcnhiLD8/PkFWWAgpKXD22XDueaWMnrCNU/tuomXHTWw5uAD+H3dv5OGXK5Zgu4p3VXjvtJQ0\nurTpUl54fbbLZ7mk1yWVSrAubbrQpkWbhvojkiRJkiRJjYxlmRpEYWEhucNyWXHGCriM8gXh7/3g\nXl4a9hL5L+VXKMz274+vLZafD3/N382idzay9pNNkLmJrG6bOOmMTfT+4kbS2m2iKG0TyUXXIgAA\nIABJREFUW/ZuYtaeLZSuK4V1hz+3Q6sO5UXXyW1PJueknIqL4R8swk5ofQIpQUrC/1wkSZIkSVLj\nZlmmBvGD/+8HrDh9BZxxxMEAwjNCVpSt4OJvDefUCy5i5bpNrPlkE5+UbCRsEy/HOGNPhfv2p7ak\nOLMrHcp3f8yttAbYSVkn0aVNF1qmtUz49ypJkiRJkpoOyzI1iMf+8Dh8o5qTvWHRI39h0anLabG/\nKydkdWVQh9M46+TPc3Z2V7q3r1iCtWvZzjWyJEmSJElSQliWqd6FYcje0qL4o5dVCSBlf0s23LaZ\nLl0swSRJkiRJUuPhok1qGEUpEFZzLoSgKIXOnROaSJIkSZIk6agsy1TvgiAgIzgR/lHNP17/SCEj\nONFHKyVJkiRJUqNjWaYGce2/Xgcvt4V/cHjCLARWpsAzPbjuqusjTCdJkiRJklQ11yxTg5j0y//H\n/em/hpe7w3Np0KoEitJhX3/O6lnIXXf9Z9QRJUmSJEmSKnGyTA3i/r/8CToWM/Ssr9Kz3el0CwbS\ns93pjPv2ABYv/l+ysrKijihJkiRJklSJk2VqEL/6a4zWe7/AX5+8n9TU+A6ZrlEmSZIkSZIaO8sy\n1bsn/1rAPzNfY0zPeaSmxo9ZlEmSJEmSpGTgY5iqd//vDzFSd5/Cr751edRRJEmSJEmSasWyTPVq\n0dubWd3mcYZ3vpXWLR1clCRJkiRJycWyTPVqzEMzIExj2re+FXUUSZIkSZKkWrMsU735YHUxf0+9\nj8+1voFuHTpEHUeSJEmSJKnWLMtUb8bc+yRkbmbqdeOijiJJkiRJklQnlmWqF5s2hby0O0YvLmZQ\nzz5Rx5EkSZIkSaoTV2BXvfj+lNcJT1pK3vBno44iSZIkSZJUZ06W6bh98gk8sTrGCWW9+fqAr0Qd\nR5IkSZIkqc4sy3TcfjFlLQfO+D23nT+WlMB/pCRJkiRJUvKy2dBx2b0bpr8xjRa0Yex5N0YdR5Ik\nSZIk6bhYlum4TLlvL0Wf+Q03nP1NslpmRR1HkiRJkiTpuFiWqc6KiuCXz82BVjv40ZdvjTqOJEmS\nJEnScbMsU509+GDIrj5TGNbjMk7rcFrUcSRJkiRJko6bZZnqpKQEfj7nT9D5Xf7zwvFRx5EkSZIk\nSaoXlmWqkzlzYEt2jN7t+vPFnl+MOo4kSZIkSVK9sCxTrZWWws+mfgC9n+X288cRBEHUkSRJkiRJ\nkuqFZZlqbd48+LjLVNq1OIFrz7426jiSJEmSJEn1xrJMtRKG8N937SJ10EPckvsdWqe3jjqSJEmS\nJElSvbEsU6088wy822IWpO9jzOAxUceRJEmSJEmqV2lRB1DyCEP4RV4prS6YyhWfuZqT254cdSRJ\nkiRJkqR6ZVmmY/byy7B4x7OQsYrxuY9GHUeSJEmSJKneWZbpmOXlQdawGH26DeFz3T8XdRxJkiRJ\nkqR655plOiYLF8Ir775NYaeX+Y/P/UfUcSRJkiRJkhqEk2U6Jnl50P4rU8jI6sbVfa+OOo4kSZIk\nSVKDcLJMR7VsGTz7yjb29JrDmEFjSE9NjzqSJEmSJElSg7As01FNnAgdhs0kJSXk2znfjjqOJEmS\nJElSg7EsU41WrIDf/b6EcNA0rjv7Ojq16RR1JEmSJEmSpAZjWaYa3XkndDj39+woW8/4z42POo4k\nSZIkSVKDsixTtT76CB59FNpdHOOLPb9I/y79o44kSZIkSZLUoOpUlgVBcEsQBB8FQbAvCIJFQRAM\nPsb7Ph8EQUkQBAV1+Vwl1l13QeaZS1hdupDxuU6VSZIkSZKkpq/WZVkQBNcAk4GfAgOAN4HngyDo\neJT72gG/BV6qQ04l2IYNMGsW9LwmRnb7bIb3Hh51JEmSJEmSpAZXl8myCcD9YRjODsPwPeBmYC8w\n6ij3zQAeBRbV4TOVYJMnQ8uOG1kePMmtQ24lNSU16kiSJEmSJEkNrlZlWRAE6UAO8KdDx8IwDIlP\niw2t4b6bgGzgZ3WLqUTatg1mzIDPfus+WqS2YNSAo/WgkiRJkiRJTUNaLa/vCKQCmz91fDNwZlU3\nBEFwBjAROC8Mw7IgCGodUokVi0GYWsR7bWbwjX7foH2r9lFHkiRJkiRJSogG3Q0zCIIU4o9e/jQM\nww8PHW7Iz9Tx2bkTpk6F88c8zrZ9Wxk7ZGzUkSRJkiRJkhKmtpNl24BSoMunjncBNlVxfRYwCDgn\nCIJpB4+lAEEQBPuBi8Mw/HN1HzZhwgTatWtX4djIkSMZOXJkLWPrWE2fDnv3hazrHuNfOvwLZ3as\ncmBQkiRJkiSp3s2dO5e5c+dWOLZz586EZgjiS47V4oYgWATkh2E4/uDrAFgDTAnD8O5PXRsAfT71\nFrcAXwKuAlaHYbivis8YCCxdunQpAwcOrFU+1d3evdCzJwwd8SoLTryAP173Ry45/ZKoY0mSJEmS\npGasoKCAnJwcgJwwDAsa+vNqO1kG8D/Aw0EQLAUWE98dMwN4GCAIgklAtzAMbzy4+P/yI28OgmAL\nUBSG4YrjCa76N3MmbN8OxQNinLX3LC7udXHUkSRJkiRJkhKq1mVZGIZPBkHQEfg58ccvlwGXhGG4\n9eAlXYEe9RdRiVBcDHffDZffuJr5a+dz77/ci5sxSJIkSZKk5qYuk2WEYTgdmF7NuZuOcu/PgJ/V\n5XPVcGbPhg0boP1F02j7cVtu+OwNUUeSJEmSJElKuAbdDVPJ4cABuPNOuPzqPfz+4wf41oBv0aZF\nm6hjSZIkSZIkJZxlmXj8cVi1CvqMmM2u4l3cOuTWqCNJkiRJkiRFwrKsmSsrg0mT4F++WsYfNk7h\nirOu4NT2p0YdS5IkSZIkKRKWZc3c/PmwfDkM+84LvLftPcbnjo86kiRJkiRJUmQsy5qxMIS8PPjS\nl+DFwhjndD2HL5zyhahjSZIkSZIkRcayrBl7/nkoKIB/n/Aef/zgj4zPHU8QBFHHkiRJkiRJioxl\nWTOWlwe5ubAkZSqd23RmRL8RUUeSJEmSJEmKVFrUARSNV1+F116Dx36/g9Fv/pbbht5Gq7RWUceS\nJEmSJEmKlJNlzVReHvTvD+u7PMj+0v18d/B3o44kSZIkSZIUOSfLmqElS+CFF+CxuaX855J7uabf\nNXTN7Bp1LEmSJEmSpMg5WdYMTZwIvXtDi7MXsHrHasbnjo86kiRJkiRJUqPgZFkz8847MH8+zJoF\nU5fEOLfHuQzqNijqWJIkSZIkSY2Ck2XNzKRJcMop0O+iZfzl4784VSZJkiRJknQEJ8uakQ8+gMcf\nhylT4L6lU+jetjtXnnVl1LEkSZIkSZIaDSfLmpE774ROnWD4iK089vZj3DL4FtJT06OOJUmSJEmS\n1GhYljUTa9fC7Nlw220w+937SQlSGD1wdNSxJEmSJEmSGhUfw2wm7r4bsrJg1Oj9nP3gdK7vfz0n\nZpwYdSxJkiRJkqRGxcmyZmDzZpg5E8aPh+fXzmPj7o2Myx0XdSxJkiRJkqRGx8myZuCeeyA9HcaO\nha88FePL2V+mX+d+UceSJEmSJElqdCzLmrhPPoHp02HMGFi5ZxGL1y9mwYgFUceSJEmSJElqlHwM\ns4mbOhVKSmDCBIjlx+jVoRdf6/21qGNJkiRJkiQ1SpZlTdju3RCLwejRcKD1euYtn8fYIWNJCfxr\nlyRJkiRJqoqtSRM2YwYUFsIPfgDTl0yndVprbhpwU9SxJEmSJEmSGi3LsiaqqAgmT4YbboCOXfdx\n/9L7uemcm2jbsm3U0SRJkiRJkhoty7ImatYs2LIFfvhDeOztx9i+bztjc8dGHUuSJEmSJKlRsyxr\ngkpK4Je/hGuugV69QmL5Mb7W+2ucfsLpUUeTJEmSJElq1NKiDqD6N2cOrFkDzz4Lf179Z97e8jb/\nc8n/RB1LkiRJkiSp0XOyrIkpLYVJk+Dyy6FfP/h1/q/5TKfP8OXsL0cdTZIkSZIkqdFzsqyJmTcP\n3n8fHn0UPtz+IU+vfJoZl84gCIKoo0mSJEmSJDV6TpY1IWEIEyfCxRfD4MFw7+J76dC6A9f3vz7q\naJIkSZIkSUnBybIm5Jln4K23YOpUKCwuZNayWYwZNIaM9Iyoo0mSJEmSJCUFJ8uaiDCEvDw47zw4\n/3x4eNnD7Nm/hzGDx0QdTZIkSZIkKWk4WdZEvPwy5OfDc89BWVjG1MVTuarvVfRo1yPqaJIkSZIk\nSUnDsqyJyMuDnBy45BL4v/ef4/3t7/PwFQ9HHUuSJEmSJCmpWJY1AQsXwiuvwFNPQRBALD/GoG6D\nGNp9aNTRJEmSJEmSkoplWROQlwd9+8IVV8Dyrct5cdWLPHLlIwRBEHU0SZIkSZKkpGJZluSWLYNn\nn4VHHoGUFJiSP4WumV35t8/8W9TRJEmSJEmSko67YSa5iRPhtNNgxAjYvm87s9+czXcHfZcWqS2i\njiZJkiRJkpR0nCxLYu+9B/PmwYwZkJYGD+Q/QGlYyndyvhN1NEmSJEmSpKTkZFkSmzQJunWDG2+E\nA2UHuHfxvYzsN5IumV2ijiZJkiRJkpSULMuS1EcfwaOPwve/Dy1bwvz35rN211rG546POpokSZIk\nSVLSsixLUnfdBR06wOjR8dex/BhfOOULDDhpQLTBJEmSJEmSkphlWRLasAFmzYLvfQ/atIGCjQW8\ntuY1p8okSZIkSZKOk2VZEpo8GVq3hjFj4q9j+TFOaXcKl591ebTBJEmSJEmSkpxlWZLZti2+++XY\nsdCuHWzevZnH33mcWwffSlqKm5tKkiRJkiQdD8uyJBOLxb+OP/jE5Yw3ZpCWksa3Bn4rulCSJEmS\nJElNhGVZEtm5E6ZOhZtvho4dofhAMfe9cR839L+BDq07RB1PkiRJkiQp6VmWJZHp02HfPrjttvjr\nJ999ks17NjMud1y0wSRJkiRJkpoIy7IksXcv3HMPjBoF3bpBGIbE8mNc3Oti+nTqE3U8SZIkSZKk\nJsEV4ZPEzJmwfTvcfnv89etrX2fpxqU8e+2z0QaTJEmSJElqQpwsSwLFxXD33XDddZCdHT8Wy4/R\n+8TefOX0r0QbTpIkSZIkqQmxLEsCs2fDhg3wox/FX6/ZuYbfr/g9Y4eMJSXwr1CSJEmSJKm+2LQ0\ncgcOwJ13wlVXwVlnxY9NWzyNNi3acONnb4w2nCRJkiRJUhPjmmWN3OOPw6pVMG9e/PWe/XuYWTCT\nbw74Jlkts6INJ0mSJEmS1MQ4WdaIlZXBpEnwta/BgAHxY3PemsPO4p2MHTI22nCSJEmSJElNkJNl\njdj8+bB8OTzwQPx1GIZMWTyFy868jOwO2dGGkyRJkiRJaoKcLGukwhDy8uBLX4KhQ+PHXlr1Esu3\nLmd87vhow0mSJEmSJDVRTpY1Us8/DwUF8NJLh4/F8mP079KfC069ILpgkiRJkiRJTZhlWSOVlwe5\nuXDhhfHX7//zfZ59/1kevOxBgiCINpwkSZIkSVITZVnWCL36Krz2GixYAId6samLp9IxoyPXnn1t\ntOEkSZIkSZKaMNcsa4Ty8qB/f7j00vjrnUU7eWjZQ3wn5zu0SmsVbThJkiRJkqQmzMmyRmbJEnjh\nBXj88cNTZQ8te4iiA0WMGTwm2nCSJEmSJElNnJNljczEidC7N1x9dfx1aVkpUxdP5et9v063rG7R\nhpMkSZIkSWrinCxrRN55B+bPh1mzIDU1fuzZ959l1SereOxfH4s2nCRJkiRJUjPgZFkjMmkSnHIK\nXH/94WOx/Bi5J+eS2z03umCSJEmSJEnNhJNljcQHH8TXKZsyBdLT48fe3vw2L3/0slNlkiRJkiRJ\nCeJkWSNx553QqROMGnX42JT8KXTL6sbVfa+OLpgkSZIkSVIzYlnWCKxdC7Nnw/e/D61bx49t27uN\nOW/PYcygMaSnpkcbUJIkSZIkqZmwLGsE7r4bsrLg5psPH5u5dCZhGPLtnG9HF0ySJEmSJKmZsSyL\n2ObNMHMmjB8PmZnxYyWlJUxbMo3rzr6OTm06RRtQkiRJkiSpGbEsi9g998QX9B879vCx36/4PesL\n1zP+c+OjCyZJkiRJktQMWZZF6JNPYPp0GDMGOnQ4fDyWH+OLPb9I/y79owsnSZIkSZLUDKVFHaA5\nmzoVSkpgwoTDx5asX8LCdQv5wzV/iC6YJEmSJElSM+VkWUR274ZYDEaPhi5dDh+P5cfIbp/N8N7D\nowsnSZIkSZLUTNWpLAuC4JYgCD4KgmBfEASLgiAYXMO1nw+C4LUgCLYFQbA3CIIVQRD8R90jNw0z\nZkBhIfzgB4ePbSzcyJPvPsmtQ24lNSU1unCSJEmSJEnNVK0fwwyC4BpgMvBtYDEwAXg+CILeYRhu\nq+KWPcBU4K2Dvz8P+E0QBLvDMHygzsmTWFERTJ4MN9wAPXocPn7fG/fRIrUFowaMii6cJEmSJElS\nM1aXybIJwP1hGM4Ow/A94GZgL1BlwxOG4bIwDJ8Iw3BFGIZrwjB8DHge+EKdUye5WbNgyxb44Q8P\nHys6UMSMN2bwjXO+QftW7aMLJ0mSJEmS1IzVqiwLgiAdyAH+dOhYGIYh8BIw9BjfY8DBa/9cm89u\nKkpK4K674Jpr4PTTDx+f+/Zctu7dytghY6MLJ0mSJEmS1MzV9jHMjkAqsPlTxzcDZ9Z0YxAEa4FO\nB+//rzAMH6rlZzcJjz4KH38Mzzxz+FgYhsTyY3z1jK9yZsca/xglSZIkSZLUgGq9ZtlxOA/IBD4H\n/DIIgg/CMHyiphsmTJhAu3btKhwbOXIkI0eObLiUDai0FCZOhMsvh379Dh9/9eNXeXPzm9x10V3R\nhZMkSZIkSYrY3LlzmTt3boVjO3fuTGiGIP4U5TFeHH8Mcy9wVRiGC444/jDQLgzDK4/xfe4Arg/D\nsE815wcCS5cuXcrAgQOPOV9j98QTMGIELF4Mg4/YP/Rfn/hX3tv2Hu+OeZcgCKILKEmSJEmS1MgU\nFBSQk5MDkBOGYUFDf16t1iwLw7AEWAp8+dCxIN7ufBl4vRZvlQq0rM1nJ7swjE+VXXxxxaJs9Y7V\n/O/K/2Vc7jiLMkmSJEmSpIjV5THM/wEeDoJgKbCY+O6YGcDDAEEQTAK6hWF448HXY4A1wHsH778A\nuA349XElTzLPPANvvQVTp1Y8fu/ie2nbsi3/3v/fowkmSZIkSZKkcrUuy8IwfDIIgo7Az4EuwDLg\nkjAMtx68pCvQ44hbUoBJQE/gAPAh8IMwDH9zHLmTShhCXh6cdx6cf/7h47v37+aBggf4ds63adOi\nTXQBJUmSJEmSBNRxgf8wDKcD06s5d9OnXt8L3FuXz2kqXn4Z8vPhuecqHp/95mwK9xdyy+Bbogkm\nSZIkSZKkCmq1ZpnqJi8PcnLgkksOHysLy5iSP4Urz7qSU9ufGl04SZIkSZIklavTZJmO3cKF8Mor\n8NRTcOT6/S98+AIr/7mSmcNnRhdOkiRJkiRJFThZ1sDy8qBvX7jiiorHY/kxBnQdwHmnnBdNMEmS\nJEmSJFXiZFkDWrYMnn0WHnkEUo6oJd/b9h5//OCPPHz5wwRHjptJkiRJkiQpUk6WNaCJE+G002DE\niIrHp+ZPpXObzozoN6LqGyVJkiRJkhQJJ8sayHvvwbx5MGMGpB3xp7yjaAe/ffO33Db0NlqmtYwu\noCRJkiRJkipxsqyB3HkndOsGN95Y8fiDBQ+yv3Q/3x383WiCSZIkSZIkqVpOljWAjz6COXNg8mRo\necTwWGlZKfcuuZdr+l1D18yu0QWUJEmSJElSlSzLGsBdd8EJJ8Do0RWPL1i5gNU7VvO7r/8ummCS\nJEmSJEmqkY9h1rMNG2DWLJgwATIyKp6L5cc4t8e5DOo2KJpwkiRJkiRJqpGTZfVs8mRo3RrGjKl4\nfNmmZfzl47/wxNVPRBNMkiRJkiRJR+VkWT3ati2+++XYsdCuXcVzU/Kn0L1td64868powkmSJEmS\nJOmoLMvqUSwW/zp+fMXjW/ds5bG3H+OWwbeQnpqe+GCSJEmSJEk6JpZl9WTnTpg6FW6+GTp2rHju\n/qX3kxKkMHrg6KpvliRJkiRJUqNgWVZPpk+HffvgttsqHt9fup/pS6Zzff/rOTHjxGjCSZIkSZIk\n6ZhYltWDvXvhnntg1Cjo1q3iuXnL57Fx90bG5Y6LJpwkSZIkSZKOmWVZPZg5E7Zvh9tvr3g8DEN+\nvejXfDn7y/Tr3C+acJIkSZIkSTpmaVEHSHbFxXD33XDddZCdXfHconWLWLJhCQtGLIgmnCRJkiRJ\nkmrFybLjNHs2bNgAP/pR5XOx/Bi9OvTia72/lvhgkiRJkiRJqjXLsuNw4ADceSdcdRWcdVbFc+t2\nrWPe8nmMyx1HSuAfsyRJkiRJUjLwMczj8PjjsGoVPPVU5XPTl0wnIz2Db5zzjYTnkiRJkiRJUt04\n8lRHZWUwaRJ87WtwzjkVz+0r2cdvlv6GUQNG0bZl22gCSpIkSZIkqdacLKuj+fNh+XJ44IHK5x59\n+1G279vO2CFjEx9MkiRJkiRJdeZkWR2EIeTlwZe+BEOHfvpcSCw/xqW9L6XXCb2iCShJkiRJkqQ6\ncbKsDp5/HgoK4KWXKp97ZfUrvLPlHX59ya8TH0ySJEmSJEnHxcmyOsjLg9xcuPDCyudi+TH6de7H\nhdlVnJQkSZIkSVKj5mRZLb36Krz2GixYAEFQ8dyH2z/k6ZVPc/+l9xN8+qQkSZIkSZIaPSfLaikv\nD/r3h0svrXzu3sX30qF1B67rf13ig0mSJEmSJOm4OVlWC0uWwAsvwOOPV54qKywuZNayWYwZNIaM\n9IxoAkqSJEmSJOm4OFlWCxMnQu/ecPXVlc89vOxh9uzfw5jBYxIfTJIkSZIkSfXCybJj9M47MH8+\nzJoFqakVz5WFZUxdPJWr+l5Fj3Y9ogkoSZIkSZKk42ZZdowmTYJTToHrr6987rn3n+P97e/z8BUP\nJzyXJEmSJEmS6o9l2TH44IP4OmVTpkB6euXzsfwYg7oNYmj3oYkPJ0mSJEmSpHpjWXYM7rwTOneG\nUaMqn1u+dTkvrnqRR658hODTq/5LkiRJkiQpqbjA/1GsXQuzZ8Ntt0Hr1pXPT8mfQtfMrvzbZ/4t\n8eEkSZIkSZJUryzLjuLuuyErC26+ufK57fu2M/vN2Xx30Hdpkdoi8eEkSZIkSZJUryzLarB5M8yc\nCePHQ2Zm5fMPFDxAaVjKd3K+k/hwkiRJkiRJqneWZTW45574gv5jx1Y+d6DsAPcuvpeR/UbSJbNL\n4sNJkiRJkiSp3lmWVeOTT2D6dBgzBjp0qHx+/nvzWbtrLeNzxyc+nCRJkiRJkhqEZVk1pk6FkhKY\nMKHq87H8GF845QsMOGlAYoNJkiRJkiSpwaRFHaAx2r0bYjEYPRq6VPGEZcHGAl5b8xrzvj4v8eEk\nSZIkSZLUYJwsq8KMGVBYCD/4QdXnY/kxTml3CpefdXlig0mSJEmSJKlBWZZ9SlERTJ4MN9wAPXpU\nPr9p9ybmvj2XsUPGkpbiYJ4kSZIkSVJTYln2KbNmwZYt8MMfVn1+xhszSE9N55sDvpnYYJIkSZIk\nSWpwlmVHKCmBu+6Ca66B00+vfL74QDH3vXEfN372Rjq0rmKLTEmSJEmSJCU1nyM8wqOPwscfwzPP\nVH3+iXefYMueLYzLHZfYYJIkSZIkSUoIJ8sOKi2FSZPgiiugX7/K58MwJJYf45Jel3BWx7MSH1CS\nJEmSJEkNzsmyg+bNg3/8Iz5dVpW/rf0bBRsL+L9r/y+xwSRJkiRJkpQwTpYBYQgTJ8LFF8OgQVVf\nE8uP0fvE3lxy+iWJDSdJkiRJkqSEcbKM+Bplb70FU6dWfX7NzjX8YcUfiH0lRkpgvyhJkiRJktRU\nNfvmJwwhLw/OOw/OP7/qa6YtnkZmi0xuPOfGxIaTJEmSJElSQjX7ybKXX4b8fHjuuarP79m/h5kF\nM/nmgG+S2SIzseEkSZIkSZKUUM1+siwvD3Jy4JJqliKb89Ycdhbv5NYhtyY2mCRJkiRJkhKuWU+W\nLVwIr7wCTz0FQVD5fBiGTFk8hcvOvIzsDtmJDyhJkiRJkqSEataTZXl50LcvXHFF1edfWvUSy7cu\nZ3zu+MQGkyRJkiRJUiSa7WTZsmXw7LPwyCOQUk1lGMuP0b9Lfy449YLEhpMkSZIkSVIkmm1ZNnEi\nnHYajBhR9fn3//k+z77/LA9e9iBBVc9oSpIkSZIkqclplmXZe+/BvHkwYwakVfMnMHXxVDpmdOTa\ns69NbDhJkiRJkiRFplmuWXbnndCtG9x4Y9Xndxbt5KFlD/GdnO/QKq1VYsNJkiRJkiQpMs1usmz1\napgzByZPhpYtq77moWUPUXSgiDGDxyQ0myRJkiRJkqLV7CbLfvlLOOEEGD266vOlZaVMXTyVr/f9\nOt2yuiU2nCRJkiRJkiLVrMqyDRtg1iyYMAEyMqq+5tn3n2XVJ6sYnzs+seEkSZIkSZIUuWZVlk2e\nDK1bw5ganq6M5cfIPTmX3O65iQsmSZIkSZKkRqHZrFm2bVt898vvfQ/atav6mrc3v83LH73MY//6\nWGLDSZIkSZIkqVFoNpNlsVj86/ganq6ckj+FblnduLrv1YkJJUmSJEmSpEalWZRlO3fC1Klw883Q\nsWPV12zbu405b89hzKAxpKemJzagJEmSJEmSGoVmUZZNnw779sFtt1V/zcylMwH4ds63E5RKkiRJ\nkiRJjU2TL8v27oV77oFRo6Bbt6qvKSktYdqSaVx39nV0atMpsQElSZIkSZLUaDT5smzmTNi+HW6/\nvfprnlrxFOsL1zM+t4YFzSRJkiRJktTkNemyrLgY7r4brrsOsrOrvy6WH+NLPb/E2V3OTlw4SZIk\nSZIkNTppUQdoSLNnw4YN8KMfVX/N4vWLWbRuEfOvmZ+4YJIkSZIkSWqUmuxk2YEDcOedcPXVcNZZ\n1V8Xy4+R3T6bS3tfmrhwkiRJkiRJapSa7GTZE0/AqlXw1FPVX7OhcANPvvskdw23C2CJAAAdSUlE\nQVS7i9SU1MSFkyRJkiRJUqNUp8myIAhuCYLgoyAI9gVBsCgIgsE1XHtlEAQvBEGwJQiCnUEQvB4E\nwcV1j3x0ZWUwcSJ87WtwzjnVX3ffkvtoldaKUQNGNWQcSZIkSZIkJYlal2VBEFwDTAZ+CgwA3gSe\nD4KgYzW3nA+8APwLMBB4BXg6CILP1inxMZg/H5YvhzvuqP6aogNF3L/0fr7x2W/QrlW7hooiSZIk\nSZKkJFKXybIJwP1hGM4Ow/A94GZgL1DleFYYhhPCMPxVGIZLwzD8MAzDO4D3geF1Tl2DMIS8PPjS\nl2Do0Oqvm/v2XLbu3crY3LENEUOSJEmSJElJqFZrlgVBkA7kABMPHQvDMAyC4CWghmqqwnsEQBaw\nvTaffayefx4KCuCll6q/JgxDYvkxvnrGV+l9Yu+GiCFJkiRJkqQkVNvJso5AKrD5U8c3A12P8T1+\nALQBnqzlZx+TvDzIzYULL6z+mlc/fpU3N7/J+NzxDRFBkiRJkiRJSSqhu2EGQXAt8BPgsjAMt9X3\n+7/6Krz2GixYAEFQ/XWx/Bh9OvbhotMuqu8IkiRJkiRJSmK1Lcu2AaVAl08d7wJsqunGIAhGAL8B\nrg7D8JVj+bAJEybQrl3FxfdHjhzJyJEjq7w+Lw/694dLL63+PVfvWM3/rvxfpn11GkFNjZokSZIk\nSZISau7cucydO7fCsZ07dyY0QxCGYe1uCIJFQH4YhuMPvg6ANcCUMAzvruaekcADwDVhGD5zDJ8x\nEFi6dOlSBg4ceEy5liyBIUPg8cfhmmuqv+77L3yfB//+IOsmrKNNizbH9N6SJEmSJEmKRkFBATk5\nOQA5YRgWNPTn1eUxzP8BHg6CYCmwmPjumBnAwwBBEEwCuoVheOPB19cePDcOWBIEwaGptH1hGO46\nrvRHmDgReveGq6+u/prd+3fzQMEDfDvn2xZlkiRJkiRJqqTWZVkYhk8GQdAR+Dnxxy+XAZeEYbj1\n4CVdgR5H3DKa+KYA0w7+OuS3wKi6hP60d96B+fNh1ixITa3+utlvzqZwfyG3DL6lPj5WkiRJkiRJ\nTUydFvgPw3A6ML2aczd96vWX6vIZtTFpEpxyClx/ffXXlIVlTMmfwpVnXcmp7U9t6EiSJEmSJElK\nQgndDbMhfPBBfJ2yqVMhPb3661748AVW/nMlM4fPTFw4SZIkSZIkJZWUqAMcr1/+Ejp3hlFHeaAz\nlh9jQNcBnHfKeYkJJkmSJEmSpKST1GXZ2rXw29/CbbdBq1bVX/fetvf44wd/ZHzueOKbd0qSJEmS\nJEmVJXVZdvfdkJUFN99c83VT86fSuU1nRvQbkZhgkiRJkiRJSkpJW5Zt3gwzZ8L48ZCZWf11O4p2\n8Ns3f8vNOTfTMq1l4gJKkiRJkiQp6SRtWXbPPfEF/ceOrfm6BwseZH/pfr47+LuJCSZJkiRJkqSk\nlZRl2SefwPTpMGYMdOhQ/XWlZaXcu+ReRvQbQdfMrokLKEmSJEmSpKSUFnWAupg6FUpKYMKEmq9b\nsHIBq3esZt7X5yUmmCRJkiRJkpJa0k2W7d4NsRiMHg1dutR87a/zf83ne3yenG45iQknSZIkSZKk\npJZ0k2UzZkBhIfzgBzVft2zTMl79+FWevPrJxASTJEmSJElS0kuqybKiIpg8GW64AXr0qPnaWH6M\nHm17cGWfKxMTTpIkSZIkSUkvqcqyWbNgyxb44Q9rvm7Lni089vZj3DL4FtJSkm54TpIkSZIkSRFJ\nmrKspATuugtGjIDTT6/52vvfuJ/UIJXROaMTE06SJEmSJElNQtKMXT36KHz8MTzzTM3X7S/dz/Q3\npvPv/f+dE1qfkJhwkiRJkiQp6axZs4Zt27ZFHUNAx44dOeWUU6KOASRJWVZaCpMmwRVXQL9+NV/7\nu3d/x6bdmxiXOy4x4SRJkiRJUtJZs2YNffr0Ye/evVFHEZCRkcGKFSsaRWGWFGXZvHnwj3/Ep8tq\nEoYhsfwYw04bxmc6fyYx4SRJkiRJUtLZtm0be/fuZc6cOfTp0yfqOM3aihUruP7669m2bZtl2bEI\nQ5g4ES6+GAYNqvnaResWsWTDEp4e+XRiwkmSJEmSpKTWp08fBg4cGHUMNSKNvix75hl46y2YOvXo\n18byY5x+wul89YyvNnwwSZIkSZIkNTmNejfMMIS8PDjvPDj//JqvXbdrHfOWz2PskLGkBI3625Ik\nSZIkSVIj1agny5Ysgfx8eO65o187fcl0MtIz+MY532jwXJIkSZIkSWqaGvUI1oMPQk4OXHJJzdft\nK9nHb5b+hlEDRtG2ZdvEhJMkSZIkSVKT06jLsjfeuJkuXX7K7t2FNV736NuPsn3fdsYOGZugZJIk\nSZIkSc1Tz549GTVqVNQxGkyjLsvgPv74x6EMHXoVhYVVF2ZhGBLLj3Fp70vpdUKvBOeTJEmSJElq\nfBYuXMjPfvYzdu3aVe/vnZKSQhAE9f6+jUUjL8sCysq+wooVE/jxjydXecUrq1/hnS3vMD53fIKz\nSZIkSZKk5iQMw6R579dff52f//zn7Nixo17fF2DlypX85je/qff3bSwaeVkWV1b2FRYs+FuV52L5\nMfp17seF2RcmOJUkSZIkSWrqCgsLGTfup2RnD6NHjyvIzh7GuHE/rfYJuMby3sdavoVhSHFxca3e\nOz09ndTU1LrESgpJUZZBQElJRqW/6A+3f8jTK59m3JBxTXr8T5IkSZIkJV5hYSFDh17FtGlDWb36\nRdav/19Wr36RadNqXjIq6vf+2c9+xu233w7E1xdLSUkhNTWVjz/+mJSUFMaNG8djjz1Gv379aNWq\nFc8//zwAv/rVr/j85z9Px44dycjI4P9v7/6jo67vfI8/3wMRQWJLC5ZoRa10ra4uCij1WqwevaK1\n/KiKuOpZWt26rUa9uvd4t4W2bMGtda+hQcFydmXRrkuIULfAUaHC2msR5QpFK8ZVqli7IKj4A0H5\nlc/+MRMkIUEMSb6T5Pk4h+PMd77z+b7m6ODklc/nM4MHD2bu3Ll7jd9wz7J7772XXC7HE088wc03\n38xhhx1Gz549ueiii3jrrbea/Tqy0jXrAPsnUVKyZa9C7K7ld9Grey+u+IsrMsolSZIkSZI6qnHj\n/i81NTdTW3v+HkfrtoxKjB9/B5WVE4pu7IsvvpgXX3yRqqoqKisr+exnP0tE0KdPHwAWL15MdXU1\n5eXl9O7dm6OPPhqAKVOmMHLkSK688kq2b99OVVUVl156KQsWLOCCCy74KGUTE5auv/56PvOZzzBh\nwgTWrl3L5MmTKS8vZ9asWc16HVlpF2VZLvcII0Z8pd6xzds2M2PVDK4dfC09SnpklEySJEmSJHVU\n8+cvpbZ2QqOP1daez5w5FYwd27yx58zZ99jz5lVQWdm8sU888UQGDhxIVVUVI0eOpF+/fvUef/HF\nF3nuuec47rjj6h1/6aWX6Nat2+775eXlnHLKKVRUVNQry5rSp08fHnnkkd33d+3axZ133snmzZsp\nLS1t3ovJQJGXZYlc7mGOP34ykybVn/Y3c9VMtmzfwrWnXptRNkmSJEmS1FGllNix4xCgqW2fgnXr\nejBoUNrHOU2ODux77LrtqFpj26mzzjprr6IMqFeUvfPOO+zcuZOhQ4dSVVX1sWNGBNdcc029Y0OH\nDuVnP/sZr776KieeeOKBB28jRV2WlZVdy+jRFzBp0tx6DWRtquXO5Xdy8QkXc+SnjswwoSRJkiRJ\n6ogigpKSLeSLrcYKq0RZ2RYWLGhOmRV8/etbWL++6bEb246qpdQtu2xowYIF3Hrrraxatarepv+5\n3P5teX/kkfU7ml69egHw9ttvNy9oRoq6LFuw4G4GDhy41/GHX3qYlza9xL2j7s0glSRJkiRJ6gyG\nDz+DqVMXNthXLC+Xe4TRo79CI7XFfrnkkn2P3XA7qpbUvXv3vY49/vjjjBw5krPOOou7776bsrIy\nSkpKmDFjxn7vOdbUN2Tu7zdzFouiLsuaUvlUJacefipf/vyXs44iSZIkSZI6qFtv/d8sWXIxNTWp\nUGoF+S2jHml0y6hiGRua3oS/Kb/85S/p3r07CxcupGvXj+qie+6554BytEf7N4+uiKzeuJpfv/xr\nbhxyY6tNR5QkSZIkSSotLWXZsrmUlz/F0UefxxFHjOToo8+jvPwpli2be0Cb1rfm2ACHHHIIkN97\nbH906dKFiGDnzp27j61du5Zf/epXB5SjPWp3M8umPDWFsp5ljP7z0VlHkSRJkiRJHVxpaSmVlROo\nrKTFN9xvzbEHDRpESonvf//7XHbZZZSUlDB8+PAmz7/wwgupqKhg2LBhXH755WzYsIFp06bxxS9+\nkWefffZjr9fUUsv2tgQT2tnMsk0fbOIXz/6C7w7+Lgd1OSjrOJIkSZIkqRNpzRVuLT324MGDmTRp\nEs8++yzf+ta3uOKKK3jjjTeIiEavdfbZZzNjxgw2bNjATTfdxOzZs7n99tsZNWpUo1kbjtFU/va4\nKjCKseGLiIHAihUrVtTb4P+nv/0pP3zsh7x202scdshh2QWUJEmSJEnt2sqVKxk0aBANuwe1vY/7\nd1H3ODAopbSytfO0m5llO2t3MvX/T+Xyky63KJMkSZIkSVKraDdl2YM1D/Lae69x45Abs44iSZIk\nSZKkDqrdlGWVT1Vy5lFncnLfk7OOIkmSJEmSpA6qXXwb5op1K1j62lLmXjo36yiSJEmSJEnqwNrF\nzLLKpyo56lNHMfK4kVlHkSRJkiRJUgdW9GXZ6++/TtVzVZSfVk6XXJes40iSJEmSJKkDK/qy7OdP\n/5ySLiVcfcrVWUeRJEmSJElSB1fUZdn2ndu5++m7GTtgLL2698o6jiRJkiRJkjq4oi7LFr28iI1b\nNnLDkBuyjiJJkiRJkqROoKjLslnPzWLYscP4Uu8vZR1FkiRJkiRJnUBRl2UvvPECNw65MesYkiRJ\nkiRJ6iSKuizr8lAXHvqnh9i8eXPWUSRJkiRJkjqlmTNnksvl+OMf/5h1lDZR1GXZrq/tYtrr0zj9\nvNMtzCRJkiRJkjIQEURE1jHaTFGXZQC1x9ZS07+G8ZPGZx1FkiRJkiRJHVzRl2WQL8zmPTov6xiS\nJEmSJKkTSym1y7H1ybSLsoyAHbkd/ocjSZIkSZLa1ObNm7nhlhs4ZuAxHHnakRwz8BhuuOWGFtku\nqrXGnjt3Lrlcjscff3yvx6ZPn04ul+P555/n97//Pd/85jc59thj6d69O2VlZVx99dVs2rTpgK7f\n3nXNOsB+SVCyq6RTrY+VJEmSJEnZ2rx5M6efdzo1/WuoHVELASSY+vJUlpy3hGWLllFaWlp0Y194\n4YX07NmT6upqhg4dWu+x6upqTjrpJE444QQqKipYu3YtV111FX379mX16tVMnz6d559/nmXLljXr\n2h1Bu5hZlvtDjhH/c0TWMSRJkiRJUicybuK4fJnVv1BmAUTL7K/emmMffPDBDB8+nDlz5tRbpbdh\nwwZ+85vfMGbMGACuu+46HnvsMcaNG8fVV19NRUUFM2bMYPny5SxdurTZ12/vin5mWW5NjuPXHM+k\naZOyjiJJkiRJkjqR+Y/Oz8/6akTtsbXM+fc5jP1fY5s19pyFc6j9RtNjz5s/j0oqmzU2wJgxY6iq\nquKxxx7j7LPPBuCBBx4gpcSll14KQLdu3Xafv23bNt5//32GDBlCSomVK1dyxhlnNPv67VlRl2Vl\n/6+M0SNGM2napGZPPZQkSZIkSfqkUkrs6LLjo1lfDQWs+3Adg6YPavqcJgcHtrHPsev2bm/ullTn\nn38+hx56KLNnz95dllVXV3PyySfTv39/AN5++20mTJjA7Nmz2bhx40eXj+Ddd99t1nU7gqIuyxbc\nv4CBAwdmHUOSJEmSJHUyEUHJrpJ8sdVYX5WgrFsZC/5mQbPG//qDX2d9Wt/k2Ae6d/tBBx3EqFGj\nePDBB5k2bRrr169n6dKl3HbbbbvPGT16NE8++SS33HILAwYMoGfPntTW1jJs2DBqaxuf9dYZFHVZ\nJkmSJEmSlJXh5w5n6stTqT127+Io94cco88fzcCy5k3yuWTYJfscuyX2bh8zZgz33XcfixcvZvXq\n1QC7l2C+8847LFmyhIkTJzJu3Ljdz1mzZs0BX7e9axcb/EuSJEmSJLW1W39wK8e/dDy5Nbn8DDOA\ntMf+6uObv796a45d59xzz6VXr15UVVVRXV3NaaedxlFHHQVAly5dAPaaQTZ58uQDmtHWETizTJIk\nSZIkqRGlpaUsW7SM8ZPGM2/+PHbkdlBSW8KIc0cc8P7qrTl2na5du3LRRRdRVVXF1q1bueOOO+pd\n/8wzz+T2229n+/btHHHEESxatIi1a9fW+wbNzsiyTJIkSZIkqQmlpaVU/rSSSioPaMP9th67zpgx\nY7jnnnvI5XKMHj263mOzZs3i+uuvZ9q0aaSUGDZsGA8//DCHH354p55dZlkmSZIkSZK0H1qzQGqt\nsc855xx27drV6GNlZWXMmTNnr+MNzx87dixjx45tlXzFyD3LJEmSJEmSpALLMkmSJEmSJKnAskyS\nJEmSJEkqsCyTJEmSJEmSCizLJEmSJEmSpALLMkmSJEmSJKnAskySJEmSJEkqsCyTJEmSJEmSCrpm\nHUCSJEmSJCkrNTU1WUfo9Irt34FlmSRJkiRJ6nR69+5Njx49uPLKK7OOIqBHjx707t076xiAZZkk\nSZIkSeqE+vXrR01NDW+++WbWUUS+vOzXr1/WMQDLMkmSJEmS1En169evaAoaFY9mbfAfEddFxCsR\n8UFEPBkRp+7j3L4RcX9E/GdE7IqIiubHlVQMZs2alXUESfvge1QqXr4/peLme1QSNKMsi4gxwB3A\nj4BTgGeAhRHR1MLSbsBGYCKwqpk5JRURP0RIxc33qFS8fH9Kxc33qCRo3syym4DpKaX7UkovAN8B\ntgJXNXZySunVlNJNKaV/Bd5rflRJkiRJkiSpdX2isiwiSoBBwOK6YymlBDwKnN6y0SRJkiRJkqS2\n9UlnlvUGugAbGhzfAPRtkUSSJEmSJElSRor12zAPBqipqck6h6RGvPvuu6xcuTLrGJKa4HtUKl6+\nP6Xi5ntUKk579EMHt8X1Ir+Kcj9Pzi/D3ApcnFKat8fxmcCnUkrf+Jjn/wfwu5TSzR9z3uXA/fsd\nTJIkSZIkSR3dFSmlf2vti3yimWUppR0RsQI4B5gHEBFRuD+lBXMtBK4A1gIftuC4kiRJkiRJal8O\nBo4m3xe1uuYsw6wAZhZKs+Xkvx2zBzATICJ+AhyeUhpb94SIGAAE0BPoU7i/PaXU6DrLlNJbQKs3\nhZIkSZIkSWoXnmirC33isiylVB0RvYEfA58DVgHDUkpvFE7pCxzZ4Gm/A+rWew4ELgdeBb7QnNCS\nJEmSJElSa/hEe5ZJkiRJkiRJHVku6wCSJEmSJElSsSi6siwirouIVyLig4h4MiJOzTqTJIiI70XE\n8oh4LyI2RMSDEfFnWeeStLeI+LuIqI2IiqyzSMqLiMMj4hcR8WZEbI2IZyJiYNa5pM4uInIRMTEi\nXi68N9dExPisc0mdVUQMjYh5EfFfhc+zIxo558cRsa7wnv11RPRv6RxFVZZFxBjgDuBHwCnAM8DC\nwh5pkrI1FLgTGAKcC5QAiyKie6apJNVT+CXTNeT/HyqpCETEp4GlwDZgGHA88LfA21nmkgTA3wF/\nA1wLfAm4BbglIsozTSV1XoeQ3xv/Wj7a+363iPg/QDn5z7unAVvI90YHtWSIotqzLCKeBJ5KKd1Y\nuB/Aa8CUlNLtmYaTVE+hxN4InJlS+m3WeSRBRPQEVgDfBX4A/C6ldHO2qSRFxG3A6Smlr2adRVJ9\nETEfeD2l9O09js0BtqaU/iq7ZJIiohYYlVKat8exdcA/ppQmF+4fCmwAxqaUqlvq2kUzsywiSoBB\nwOK6Yynf5D0KnJ5VLklN+jT5pn9T1kEk7TYVmJ9SWpJ1EEn1DAeejojqwlYGKyPir7MOJQmAJ4Bz\nIuKLABExADgDeCjTVJL2EhHHAH2p3xu9BzxFC/dGXVtysAPUG+hCvhHc0wbguLaPI6kphVmfPwN+\nm1J6Pus8kiAiLgNOBgZnnUXSXr5AfsbnHcCt5JeNTImIbSmlX2SaTNJtwKHACxGxi/yEknEppaps\nY0lqRF/yEzYa6436tuSFiqksk9R+TANOIP9bN0kZi4jPky+wz00p7cg6j6S95IDlKaUfFO4/ExEn\nAt8BLMukbI0BLgcuA54n/4unyohYZ5ktdV5FswwTeBPYBXyuwfHPAa+3fRxJjYmIu4CvAWellNZn\nnUcSkN/GoA+wMiJ2RMQO4KvAjRGxvTAbVFJ21gM1DY7VAP0yyCKpvtuB21JKD6SUVqeU7gcmA9/L\nOJekvb0OBG3QGxVNWVb4TfgK4Jy6Y4UP9+eQX0cuKWOFomwkcHZK6Y9Z55G026PASeR/Gz6g8Odp\n4F+BAamYvs1H6pyWsve2IscBr2aQRVJ9PchP2thTLUX0s7KkvJTSK+RLsT17o0OBIbRwb1RsyzAr\ngJkRsQJYDtxE/i+vmVmGkgQRMQ34S2AEsCUi6tr8d1NKH2aXTFJKaQv5pSO7RcQW4K2UUsPZLJLa\n3mRgaUR8D6gm/6H+r4Fv7/NZktrCfGB8RPwJWA0MJP9z6D9nmkrqpCLiEKA/+RlkAF8ofPHGppTS\na+S3HhkfEWuAtcBE4E/Ar1o0R7H9sjkirgVuIT+NbhVwfUrp6WxTSSp8bW9jf2F8K6V0X1vnkbRv\nEbEEWJVSujnrLJIgIr5GfiPx/sArwB0ppRnZppJU+MF8IvAN4DBgHfBvwMSU0s4ss0mdUUR8FfgP\n9v7Z896U0lWFcyYA1wCfBh4HrksprWnRHMVWlkmSJEmSJElZcR22JEmSJEmSVGBZJkmSJEmSJBVY\nlkmSJEmSJEkFlmWSJEmSJElSgWWZJEmSJEmSVGBZJkmSJEmSJBVYlkmSJEmSJEkFlmWSJEmSJElS\ngWWZJEmSJEmSVGBZJkmS1MFERG1EjMg6hyRJUntkWSZJktSCIuJfCmXVrsI/624/lHU2SZIkfbyu\nWQeQJEnqgB4GvgnEHse2ZRNFkiRJn4QzyyRJklretpTSGymljXv8eRd2L5H8TkQ8FBFbI+IPEXHx\nnk+OiBMjYnHh8TcjYnpEHNLgnKsi4rmI+DAi/isipjTI0CcifhkRWyLixYgY3sqvWZIkqUOwLJMk\nSWp7PwYeAP4CuB+oiojjACKiB7AQeAsYBFwCnAvcWffkiPgucBfwc+DPgQuBFxtc44dAFXAS8BBw\nf0R8uvVekiRJUscQKaWsM0iSJHUYEfEvwJXAh3scTsA/pJRui4haYFpKqXyP5ywDVqSUyiPi28BP\ngM+nlD4sPH4BMB8oSym9ERF/Au5JKf2oiQy1wI9TShMK93sA7wPnp5QWtfBLliRJ6lDcs0ySJKnl\nLQG+Q/09yzbtcfvJBucvAwYUbn8JeKauKCtYSn5FwHERAXB44Rr78vu6GymlrRHxHnDY/r4ASZKk\nzsqyTJIkqeVtSSm90kpjf7Cf5+1ocD/hFhySJEkfyw9MkiRJbe/LjdyvKdyuAQZERPc9Hv8KsAt4\nIaX0PrAWOKe1Q0qSJHVGziyTJElqed0i4nMNju1MKb1VuD06IlYAvyW/v9mpwFWFx+4HJgD3RsTf\nk186OQW4L6X0ZuGcCcDdEfEG8DBwKPA/Ukp3tdLrkSRJ6jQsyyRJklre+cC6Bsf+EzihcPtHwGXA\nVGA9cFlK6QWAlNIHETEMqASWA1uBOcDf1g2UUrovIroBNwH/CLxZOGf3KY1k8ludJEmS9oPfhilJ\nktSGCt9UOSqlNC/rLJIkSdqbe5ZJkiRJkiRJBZZlkiRJbctp/ZIkSUXMZZiSJEmSJElSgTPLJEmS\nJEmSpALLMkmSJEmSJKnAskySJEmSJEkqsCyTJEmSJEmSCizLJEmSJEmSpALLMkmSJEmSJKnAskyS\nJEmSJEkqsCyTJEmSJEmSCizLJEmSJEmSpIL/BmSegFMgt8wwAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x49035f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Run this cell to visualize training loss and train / val accuracy\n",
    "\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.title('Training loss')\n",
    "plt.plot(solver.loss_history, 'o')\n",
    "plt.xlabel('Iteration')\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.title('Accuracy')\n",
    "plt.plot(solver.train_acc_history, '-o', label='train')\n",
    "plt.plot(solver.val_acc_history, '-o', label='val')\n",
    "plt.plot([0.5] * len(solver.val_acc_history), 'k--')\n",
    "plt.xlabel('Epoch')\n",
    "plt.legend(loc='lower right')\n",
    "plt.gcf().set_size_inches(15, 12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Multilayer network\n",
    "Next you will implement a fully-connected network with an arbitrary number of hidden layers.\n",
    "\n",
    "Read through the `FullyConnectedNet` class in the file `cs231n/classifiers/fc_net.py`.\n",
    "\n",
    "Implement the initialization, the forward pass, and the backward pass. For the moment don't worry about implementing dropout or batch normalization; we will add those features soon."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Initial loss and gradient check"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As a sanity check, run the following to check the initial loss and to gradient check the network both with and without regularization. Do the initial losses seem reasonable?\n",
    "\n",
    "For gradient checking, you should expect to see errors around 1e-6 or less."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running check with reg =  0\n",
      "Initial loss:  2.30047908977\n",
      "W1 relative error: 1.48e-07\n",
      "W2 relative error: 2.21e-05\n",
      "W3 relative error: 3.53e-07\n",
      "b1 relative error: 5.38e-09\n",
      "b2 relative error: 2.09e-09\n",
      "b3 relative error: 5.80e-11\n",
      "Running check with reg =  3.14\n",
      "Initial loss:  7.05211477653\n",
      "W1 relative error: 7.36e-09\n",
      "W2 relative error: 6.87e-08\n",
      "W3 relative error: 3.48e-08\n",
      "b1 relative error: 1.48e-08\n",
      "b2 relative error: 1.72e-09\n",
      "b3 relative error: 1.80e-10\n"
     ]
    }
   ],
   "source": [
    "np.random.seed(231)\n",
    "N, D, H1, H2, C = 2, 15, 20, 30, 10\n",
    "X = np.random.randn(N, D)\n",
    "y = np.random.randint(C, size=(N,))\n",
    "\n",
    "for reg in [0, 3.14]:\n",
    "  print('Running check with reg = ', reg)\n",
    "  model = FullyConnectedNet([H1, H2], input_dim=D, num_classes=C,\n",
    "                            reg=reg, weight_scale=5e-2, dtype=np.float64)\n",
    "\n",
    "  loss, grads = model.loss(X, y)\n",
    "  print('Initial loss: ', loss)\n",
    "\n",
    "  for name in sorted(grads):\n",
    "    f = lambda _: model.loss(X, y)[0]\n",
    "    grad_num = eval_numerical_gradient(f, model.params[name], verbose=False, h=1e-5)\n",
    "    print('%s relative error: %.2e' % (name, rel_error(grad_num, grads[name])))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "As another sanity check, make sure you can overfit a small dataset of 50 images. First we will try a three-layer network with 100 units in each hidden layer. You will need to tweak the learning rate and initialization scale, but you should be able to overfit and achieve 100% training accuracy within 20 epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(Iteration 1 / 40) loss: 2.375113\n",
      "(Epoch 0 / 20) train acc: 0.220000; val_acc: 0.097000\n",
      "(Epoch 1 / 20) train acc: 0.260000; val_acc: 0.096000\n",
      "(Epoch 2 / 20) train acc: 0.440000; val_acc: 0.138000\n",
      "(Epoch 3 / 20) train acc: 0.540000; val_acc: 0.121000\n",
      "(Epoch 4 / 20) train acc: 0.640000; val_acc: 0.163000\n",
      "(Epoch 5 / 20) train acc: 0.600000; val_acc: 0.158000\n",
      "(Iteration 11 / 40) loss: 1.278468\n",
      "(Epoch 6 / 20) train acc: 0.820000; val_acc: 0.171000\n",
      "(Epoch 7 / 20) train acc: 0.780000; val_acc: 0.171000\n",
      "(Epoch 8 / 20) train acc: 0.800000; val_acc: 0.157000\n",
      "(Epoch 9 / 20) train acc: 0.940000; val_acc: 0.201000\n",
      "(Epoch 10 / 20) train acc: 0.920000; val_acc: 0.180000\n",
      "(Iteration 21 / 40) loss: 0.437798\n",
      "(Epoch 11 / 20) train acc: 0.960000; val_acc: 0.180000\n",
      "(Epoch 12 / 20) train acc: 0.980000; val_acc: 0.204000\n",
      "(Epoch 13 / 20) train acc: 0.960000; val_acc: 0.169000\n",
      "(Epoch 14 / 20) train acc: 0.980000; val_acc: 0.175000\n",
      "(Epoch 15 / 20) train acc: 0.980000; val_acc: 0.196000\n",
      "(Iteration 31 / 40) loss: 0.085872\n",
      "(Epoch 16 / 20) train acc: 0.980000; val_acc: 0.187000\n",
      "(Epoch 17 / 20) train acc: 1.000000; val_acc: 0.177000\n",
      "(Epoch 18 / 20) train acc: 1.000000; val_acc: 0.192000\n",
      "(Epoch 19 / 20) train acc: 1.000000; val_acc: 0.175000\n",
      "(Epoch 20 / 20) train acc: 0.980000; val_acc: 0.168000\n"
     ]
    },
    {
     "data": {
      "image/png": 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QkEAFAADQkEAFAADQkEAFAADQkEA1BGqtgy4BAABoQKAakE6nk8nJwxkf35nNm+/O+PjO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\n1pxUkJa2ZAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x496e0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO: Use a three-layer Net to overfit 50 training examples.\n",
    "\n",
    "num_train = 50\n",
    "small_data = {\n",
    "  'X_train': data['X_train'][:num_train],\n",
    "  'y_train': data['y_train'][:num_train],\n",
    "  'X_val': data['X_val'],\n",
    "  'y_val': data['y_val'],\n",
    "}\n",
    "\n",
    "weight_scale = 1e-2\n",
    "learning_rate = 8e-3\n",
    "model = FullyConnectedNet([100, 100],\n",
    "              weight_scale=weight_scale, dtype=np.float64)\n",
    "solver = Solver(model, small_data,\n",
    "                print_every=10, num_epochs=20, batch_size=25,\n",
    "                update_rule='sgd',\n",
    "                optim_config={\n",
    "                  'learning_rate': learning_rate,\n",
    "                }\n",
    "         )\n",
    "solver.train()\n",
    "\n",
    "plt.plot(solver.loss_history, 'o')\n",
    "plt.title('Training loss history')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Training loss')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Now try to use a five-layer network with 100 units on each layer to overfit 50 training examples. Again you will have to adjust the learning rate and weight initialization, but you should be able to achieve 100% training accuracy within 20 epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(Iteration 1 / 40) loss: 139.150523\n",
      "(Epoch 0 / 20) train acc: 0.220000; val_acc: 0.087000\n",
      "(Epoch 1 / 20) train acc: 0.180000; val_acc: 0.110000\n",
      "(Epoch 2 / 20) train acc: 0.320000; val_acc: 0.125000\n",
      "(Epoch 3 / 20) train acc: 0.520000; val_acc: 0.137000\n",
      "(Epoch 4 / 20) train acc: 0.560000; val_acc: 0.123000\n",
      "(Epoch 5 / 20) train acc: 0.680000; val_acc: 0.130000\n",
      "(Iteration 11 / 40) loss: 2.793172\n",
      "(Epoch 6 / 20) train acc: 0.820000; val_acc: 0.133000\n",
      "(Epoch 7 / 20) train acc: 0.920000; val_acc: 0.147000\n",
      "(Epoch 8 / 20) train acc: 0.980000; val_acc: 0.149000\n",
      "(Epoch 9 / 20) train acc: 0.980000; val_acc: 0.149000\n",
      "(Epoch 10 / 20) train acc: 0.980000; val_acc: 0.150000\n",
      "(Iteration 21 / 40) loss: 0.001506\n",
      "(Epoch 11 / 20) train acc: 1.000000; val_acc: 0.149000\n",
      "(Epoch 12 / 20) train acc: 1.000000; val_acc: 0.149000\n",
      "(Epoch 13 / 20) train acc: 1.000000; val_acc: 0.149000\n",
      "(Epoch 14 / 20) train acc: 1.000000; val_acc: 0.148000\n",
      "(Epoch 15 / 20) train acc: 1.000000; val_acc: 0.148000\n",
      "(Iteration 31 / 40) loss: 0.000920\n",
      "(Epoch 16 / 20) train acc: 1.000000; val_acc: 0.147000\n",
      "(Epoch 17 / 20) train acc: 1.000000; val_acc: 0.147000\n",
      "(Epoch 18 / 20) train acc: 1.000000; val_acc: 0.148000\n",
      "(Epoch 19 / 20) train acc: 1.000000; val_acc: 0.148000\n",
      "(Epoch 20 / 20) train acc: 1.000000; val_acc: 0.148000\n"
     ]
    },
    {
     "data": {
      "image/png": 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Zwms6ySVJfrTPEAEAAJaPhUTWvZI8ZI7tD0ly7Ojrb2a4rBAAAOCospDIekuS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\nIhgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xbd6a160>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# TODO: Use a five-layer Net to overfit 50 training examples.\n",
    "\n",
    "num_train = 50\n",
    "small_data = {\n",
    "  'X_train': data['X_train'][:num_train],\n",
    "  'y_train': data['y_train'][:num_train],\n",
    "  'X_val': data['X_val'],\n",
    "  'y_val': data['y_val'],\n",
    "}\n",
    "\n",
    "weight_scale = 1e-1\n",
    "learning_rate = 1e-3\n",
    "\n",
    "model = FullyConnectedNet([100, 100, 100, 100],\n",
    "                weight_scale=weight_scale, dtype=np.float64)\n",
    "solver = Solver(model, small_data,\n",
    "                print_every=10, num_epochs=20, batch_size=25,\n",
    "                update_rule='sgd',\n",
    "                optim_config={\n",
    "                  'learning_rate': learning_rate,\n",
    "                }\n",
    "         )\n",
    "solver.train()\n",
    "\n",
    "plt.plot(solver.loss_history, 'o')\n",
    "plt.title('Training loss history')\n",
    "plt.xlabel('Iteration')\n",
    "plt.ylabel('Training loss')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Inline question: \n",
    "Did you notice anything about the comparative difficulty of training the three-layer net vs training the five layer net?\n",
    "\n",
    "# Answer:\n",
    "[FILL THIS IN]\n",
    "While I tuning the hyperparameters of the five layer, I find the min loss is more sensitive to the weight_scale which make the loss function converge to a local minimum easily. I think this phenomenon happened beacause the high capacity of the five layer also make the five layer net's loss function more complex and harder to optimal domain than the three layer net and much more sensitive to initialization."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Update rules\n",
    "So far we have used vanilla stochastic gradient descent (SGD) as our update rule. More sophisticated update rules can make it easier to train deep networks. We will implement a few of the most commonly used update rules and compare them to vanilla SGD."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# SGD+Momentum\n",
    "Stochastic gradient descent with momentum is a widely used update rule that tends to make deep networks converge faster than vanilla stochstic gradient descent.\n",
    "\n",
    "Open the file `cs231n/optim.py` and read the documentation at the top of the file to make sure you understand the API. Implement the SGD+momentum update rule in the function `sgd_momentum` and run the following to check your implementation. You should see errors less than 1e-8."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "next_w error:  8.88234703351e-09\n",
      "velocity error:  4.26928774328e-09\n"
     ]
    }
   ],
   "source": [
    "from cs231n.optim import sgd_momentum\n",
    "\n",
    "N, D = 4, 5\n",
    "w = np.linspace(-0.4, 0.6, num=N*D).reshape(N, D)\n",
    "dw = np.linspace(-0.6, 0.4, num=N*D).reshape(N, D)\n",
    "v = np.linspace(0.6, 0.9, num=N*D).reshape(N, D)\n",
    "\n",
    "config = {'learning_rate': 1e-3, 'velocity': v}\n",
    "next_w, _ = sgd_momentum(w, dw, config=config)\n",
    "\n",
    "expected_next_w = np.asarray([\n",
    "  [ 0.1406,      0.20738947,  0.27417895,  0.34096842,  0.40775789],\n",
    "  [ 0.47454737,  0.54133684,  0.60812632,  0.67491579,  0.74170526],\n",
    "  [ 0.80849474,  0.87528421,  0.94207368,  1.00886316,  1.07565263],\n",
    "  [ 1.14244211,  1.20923158,  1.27602105,  1.34281053,  1.4096    ]])\n",
    "expected_velocity = np.asarray([\n",
    "  [ 0.5406,      0.55475789,  0.56891579, 0.58307368,  0.59723158],\n",
    "  [ 0.61138947,  0.62554737,  0.63970526,  0.65386316,  0.66802105],\n",
    "  [ 0.68217895,  0.69633684,  0.71049474,  0.72465263,  0.73881053],\n",
    "  [ 0.75296842,  0.76712632,  0.78128421,  0.79544211,  0.8096    ]])\n",
    "\n",
    "print('next_w error: ', rel_error(next_w, expected_next_w))\n",
    "print('velocity error: ', rel_error(expected_velocity, config['velocity']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Once you have done so, run the following to train a six-layer network with both SGD and SGD+momentum. You should see the SGD+momentum update rule converge faster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running with  sgd\n",
      "(Iteration 1 / 200) loss: 3.172982\n",
      "(Epoch 0 / 5) train acc: 0.121000; val_acc: 0.106000\n",
      "(Iteration 11 / 200) loss: 2.256368\n",
      "(Iteration 21 / 200) loss: 2.180894\n",
      "(Iteration 31 / 200) loss: 2.098789\n",
      "(Epoch 1 / 5) train acc: 0.271000; val_acc: 0.240000\n",
      "(Iteration 41 / 200) loss: 2.080658\n",
      "(Iteration 51 / 200) loss: 2.040536\n",
      "(Iteration 61 / 200) loss: 1.829603\n",
      "(Iteration 71 / 200) loss: 1.883715\n",
      "(Epoch 2 / 5) train acc: 0.315000; val_acc: 0.293000\n",
      "(Iteration 81 / 200) loss: 1.943460\n",
      "(Iteration 91 / 200) loss: 1.901979\n",
      "(Iteration 101 / 200) loss: 1.827220\n",
      "(Iteration 111 / 200) loss: 1.811500\n",
      "(Epoch 3 / 5) train acc: 0.349000; val_acc: 0.294000\n",
      "(Iteration 121 / 200) loss: 1.768563\n",
      "(Iteration 131 / 200) loss: 1.965277\n",
      "(Iteration 141 / 200) loss: 1.702832\n",
      "(Iteration 151 / 200) loss: 1.699803\n",
      "(Epoch 4 / 5) train acc: 0.360000; val_acc: 0.315000\n",
      "(Iteration 161 / 200) loss: 1.793433\n",
      "(Iteration 171 / 200) loss: 1.659870\n",
      "(Iteration 181 / 200) loss: 1.791729\n",
      "(Iteration 191 / 200) loss: 1.648964\n",
      "(Epoch 5 / 5) train acc: 0.412000; val_acc: 0.313000\n",
      "\n",
      "running with  sgd_momentum\n",
      "(Iteration 1 / 200) loss: 2.524273\n",
      "(Epoch 0 / 5) train acc: 0.104000; val_acc: 0.103000\n",
      "(Iteration 11 / 200) loss: 2.257656\n",
      "(Iteration 21 / 200) loss: 2.045991\n",
      "(Iteration 31 / 200) loss: 1.950310\n",
      "(Epoch 1 / 5) train acc: 0.243000; val_acc: 0.243000\n",
      "(Iteration 41 / 200) loss: 2.144247\n",
      "(Iteration 51 / 200) loss: 1.843321\n",
      "(Iteration 61 / 200) loss: 1.739997\n",
      "(Iteration 71 / 200) loss: 1.820478\n",
      "(Epoch 2 / 5) train acc: 0.405000; val_acc: 0.336000\n",
      "(Iteration 81 / 200) loss: 1.955672\n",
      "(Iteration 91 / 200) loss: 1.680756\n",
      "(Iteration 101 / 200) loss: 1.664422\n",
      "(Iteration 111 / 200) loss: 1.696228\n",
      "(Epoch 3 / 5) train acc: 0.456000; val_acc: 0.348000\n",
      "(Iteration 121 / 200) loss: 1.407459\n",
      "(Iteration 131 / 200) loss: 1.511904\n",
      "(Iteration 141 / 200) loss: 1.431066\n",
      "(Iteration 151 / 200) loss: 1.381037\n",
      "(Epoch 4 / 5) train acc: 0.507000; val_acc: 0.360000\n",
      "(Iteration 161 / 200) loss: 1.620952\n",
      "(Iteration 171 / 200) loss: 1.540388\n",
      "(Iteration 181 / 200) loss: 1.635579\n",
      "(Iteration 191 / 200) loss: 1.373540\n",
      "(Epoch 5 / 5) train acc: 0.508000; val_acc: 0.380000\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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jPBYsuH0gy5MkSZIkSdIQN+QDNPgl8PGsj6RSs1my5Mm9W44kSZIkSZKGlYIH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\n0hsEbKuGHTcz6tDzCSG0j5P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yLacEEq8muOyiy6i9Nd2nbcuWLa3P84nulwHmWaoKrWFO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\nhQWaJEmSJEmStBUWaJIkSZIkSdJW/D+TPsBImWdxtgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb9d1c50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_train = 4000\n",
    "small_data = {\n",
    "  'X_train': data['X_train'][:num_train],\n",
    "  'y_train': data['y_train'][:num_train],\n",
    "  'X_val': data['X_val'],\n",
    "  'y_val': data['y_val'],\n",
    "}\n",
    "\n",
    "solvers = {}\n",
    "\n",
    "for update_rule in ['sgd', 'sgd_momentum']:\n",
    "  print('running with ', update_rule)\n",
    "  model = FullyConnectedNet([100, 100, 100, 100, 100], weight_scale=5e-2)\n",
    "\n",
    "  solver = Solver(model, small_data,\n",
    "                  num_epochs=5, batch_size=100,\n",
    "                  update_rule=update_rule,\n",
    "                  optim_config={\n",
    "                    'learning_rate': 1e-2,\n",
    "                  },\n",
    "                  verbose=True)\n",
    "  solvers[update_rule] = solver\n",
    "  solver.train()\n",
    "  print()\n",
    "\n",
    "plt.subplot(3, 1, 1)\n",
    "plt.title('Training loss')\n",
    "plt.xlabel('Iteration')\n",
    "\n",
    "plt.subplot(3, 1, 2)\n",
    "plt.title('Training accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "\n",
    "plt.subplot(3, 1, 3)\n",
    "plt.title('Validation accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "\n",
    "for update_rule, solver in list(solvers.items()):\n",
    "  plt.subplot(3, 1, 1)\n",
    "  plt.plot(solver.loss_history, 'o', label=update_rule)\n",
    "  \n",
    "  plt.subplot(3, 1, 2)\n",
    "  plt.plot(solver.train_acc_history, '-o', label=update_rule)\n",
    "\n",
    "  plt.subplot(3, 1, 3)\n",
    "  plt.plot(solver.val_acc_history, '-o', label=update_rule)\n",
    "  \n",
    "for i in [1, 2, 3]:\n",
    "  plt.subplot(3, 1, i)\n",
    "  plt.legend(loc='upper center', ncol=4)\n",
    "plt.gcf().set_size_inches(15, 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# RMSProp and Adam\n",
    "RMSProp [1] and Adam [2] are update rules that set per-parameter learning rates by using a running average of the second moments of gradients.\n",
    "\n",
    "In the file `cs231n/optim.py`, implement the RMSProp update rule in the `rmsprop` function and implement the Adam update rule in the `adam` function, and check your implementations using the tests below.\n",
    "\n",
    "[1] Tijmen Tieleman and Geoffrey Hinton. \"Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude.\" COURSERA: Neural Networks for Machine Learning 4 (2012).\n",
    "\n",
    "[2] Diederik Kingma and Jimmy Ba, \"Adam: A Method for Stochastic Optimization\", ICLR 2015."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "next_w error:  9.52468751104e-08\n",
      "cache error:  2.64779558072e-09\n"
     ]
    }
   ],
   "source": [
    "# Test RMSProp implementation; you should see errors less than 1e-7\n",
    "from cs231n.optim import rmsprop\n",
    "\n",
    "N, D = 4, 5\n",
    "w = np.linspace(-0.4, 0.6, num=N*D).reshape(N, D)\n",
    "dw = np.linspace(-0.6, 0.4, num=N*D).reshape(N, D)\n",
    "cache = np.linspace(0.6, 0.9, num=N*D).reshape(N, D)\n",
    "\n",
    "config = {'learning_rate': 1e-2, 'cache': cache}\n",
    "next_w, _ = rmsprop(w, dw, config=config)\n",
    "\n",
    "expected_next_w = np.asarray([\n",
    "  [-0.39223849, -0.34037513, -0.28849239, -0.23659121, -0.18467247],\n",
    "  [-0.132737,   -0.08078555, -0.02881884,  0.02316247,  0.07515774],\n",
    "  [ 0.12716641,  0.17918792,  0.23122175,  0.28326742,  0.33532447],\n",
    "  [ 0.38739248,  0.43947102,  0.49155973,  0.54365823,  0.59576619]])\n",
    "expected_cache = np.asarray([\n",
    "  [ 0.5976,      0.6126277,   0.6277108,   0.64284931,  0.65804321],\n",
    "  [ 0.67329252,  0.68859723,  0.70395734,  0.71937285,  0.73484377],\n",
    "  [ 0.75037008,  0.7659518,   0.78158892,  0.79728144,  0.81302936],\n",
    "  [ 0.82883269,  0.84469141,  0.86060554,  0.87657507,  0.8926    ]])\n",
    "\n",
    "print('next_w error: ', rel_error(expected_next_w, next_w))\n",
    "print('cache error: ', rel_error(expected_cache, config['cache']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "next_w error:  0.207207036686\n",
      "v error:  4.20831403811e-09\n",
      "m error:  4.21496319311e-09\n"
     ]
    }
   ],
   "source": [
    "# Test Adam implementation; you should see errors around 1e-7 or less\n",
    "from cs231n.optim import adam\n",
    "\n",
    "N, D = 4, 5\n",
    "w = np.linspace(-0.4, 0.6, num=N*D).reshape(N, D)\n",
    "dw = np.linspace(-0.6, 0.4, num=N*D).reshape(N, D)\n",
    "m = np.linspace(0.6, 0.9, num=N*D).reshape(N, D)\n",
    "v = np.linspace(0.7, 0.5, num=N*D).reshape(N, D)\n",
    "\n",
    "config = {'learning_rate': 1e-2, 'm': m, 'v': v, 't': 5}\n",
    "next_w, _ = adam(w, dw, config=config)\n",
    "\n",
    "expected_next_w = np.asarray([\n",
    "  [-0.40094747, -0.34836187, -0.29577703, -0.24319299, -0.19060977],\n",
    "  [-0.1380274,  -0.08544591, -0.03286534,  0.01971428,  0.0722929],\n",
    "  [ 0.1248705,   0.17744702,  0.23002243,  0.28259667,  0.33516969],\n",
    "  [ 0.38774145,  0.44031188,  0.49288093,  0.54544852,  0.59801459]])\n",
    "expected_v = np.asarray([\n",
    "  [ 0.69966,     0.68908382,  0.67851319,  0.66794809,  0.65738853,],\n",
    "  [ 0.64683452,  0.63628604,  0.6257431,   0.61520571,  0.60467385,],\n",
    "  [ 0.59414753,  0.58362676,  0.57311152,  0.56260183,  0.55209767,],\n",
    "  [ 0.54159906,  0.53110598,  0.52061845,  0.51013645,  0.49966,   ]])\n",
    "expected_m = np.asarray([\n",
    "  [ 0.48,        0.49947368,  0.51894737,  0.53842105,  0.55789474],\n",
    "  [ 0.57736842,  0.59684211,  0.61631579,  0.63578947,  0.65526316],\n",
    "  [ 0.67473684,  0.69421053,  0.71368421,  0.73315789,  0.75263158],\n",
    "  [ 0.77210526,  0.79157895,  0.81105263,  0.83052632,  0.85      ]])\n",
    "\n",
    "print('next_w error: ', rel_error(expected_next_w, next_w))\n",
    "print('v error: ', rel_error(expected_v, config['v']))\n",
    "print('m error: ', rel_error(expected_m, config['m']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "Once you have debugged your RMSProp and Adam implementations, run the following to train a pair of deep networks using these new update rules:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running with  adam\n",
      "(Iteration 1 / 200) loss: 2.721424\n",
      "(Epoch 0 / 5) train acc: 0.134000; val_acc: 0.113000\n",
      "(Iteration 11 / 200) loss: 2.202307\n",
      "(Iteration 21 / 200) loss: 2.200554\n",
      "(Iteration 31 / 200) loss: 2.029114\n",
      "(Epoch 1 / 5) train acc: 0.348000; val_acc: 0.293000\n",
      "(Iteration 41 / 200) loss: 1.872584\n",
      "(Iteration 51 / 200) loss: 1.911158\n",
      "(Iteration 61 / 200) loss: 1.905196\n",
      "(Iteration 71 / 200) loss: 1.760092\n",
      "(Epoch 2 / 5) train acc: 0.357000; val_acc: 0.314000\n",
      "(Iteration 81 / 200) loss: 1.735753\n",
      "(Iteration 91 / 200) loss: 1.839110\n",
      "(Iteration 101 / 200) loss: 1.709435\n",
      "(Iteration 111 / 200) loss: 1.739040\n",
      "(Epoch 3 / 5) train acc: 0.404000; val_acc: 0.328000\n",
      "(Iteration 121 / 200) loss: 1.704484\n",
      "(Iteration 131 / 200) loss: 1.544026\n",
      "(Iteration 141 / 200) loss: 1.572505\n",
      "(Iteration 151 / 200) loss: 1.586239\n",
      "(Epoch 4 / 5) train acc: 0.431000; val_acc: 0.335000\n",
      "(Iteration 161 / 200) loss: 1.661597\n",
      "(Iteration 171 / 200) loss: 1.550715\n",
      "(Iteration 181 / 200) loss: 1.479263\n",
      "(Iteration 191 / 200) loss: 1.361996\n",
      "(Epoch 5 / 5) train acc: 0.443000; val_acc: 0.361000\n",
      "\n",
      "running with  rmsprop\n",
      "(Iteration 1 / 200) loss: 2.747301\n",
      "(Epoch 0 / 5) train acc: 0.127000; val_acc: 0.119000\n",
      "(Iteration 11 / 200) loss: 2.068703\n",
      "(Iteration 21 / 200) loss: 2.009060\n",
      "(Iteration 31 / 200) loss: 2.020174\n",
      "(Epoch 1 / 5) train acc: 0.351000; val_acc: 0.291000\n",
      "(Iteration 41 / 200) loss: 1.794300\n",
      "(Iteration 51 / 200) loss: 1.730632\n",
      "(Iteration 61 / 200) loss: 1.771812\n",
      "(Iteration 71 / 200) loss: 1.724894\n",
      "(Epoch 2 / 5) train acc: 0.390000; val_acc: 0.332000\n",
      "(Iteration 81 / 200) loss: 1.729982\n",
      "(Iteration 91 / 200) loss: 1.656668\n",
      "(Iteration 101 / 200) loss: 1.822102\n",
      "(Iteration 111 / 200) loss: 1.681434\n",
      "(Epoch 3 / 5) train acc: 0.457000; val_acc: 0.339000\n",
      "(Iteration 121 / 200) loss: 1.566029\n",
      "(Iteration 131 / 200) loss: 1.453335\n",
      "(Iteration 141 / 200) loss: 1.495466\n",
      "(Iteration 151 / 200) loss: 1.443880\n",
      "(Epoch 4 / 5) train acc: 0.478000; val_acc: 0.371000\n",
      "(Iteration 161 / 200) loss: 1.560562\n",
      "(Iteration 171 / 200) loss: 1.427810\n",
      "(Iteration 181 / 200) loss: 1.440717\n",
      "(Iteration 191 / 200) loss: 1.352276\n",
      "(Epoch 5 / 5) train acc: 0.522000; val_acc: 0.329000\n",
      "\n"
     ]
    },
    {
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xv+HJJw+q9tc7prJfYXh5LC+1nlB1+Mw+eYKN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VU5OcxITWVBcjIzUlNZlZOj6HO9l478/CWkp69FFLfjeZ+eo0f1rsVxVksk8lNbwE3OjJXJGVCu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\nBce8UgYU2u2zqamRmDmzktoD7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JbB0Zr18IT6WEgMwliuN0EQTN/nWtdkoJeSzfnfKmo7\nyy2wqBafsOFSUaRg3DjGCp2kXpdKd1g3A3oGMLqpyXB7jOSjaq1vZNSo+UREtJOVlcmOg5+x6Ef3\nsfTIQeLt0CrCsAmT+GTbJh/Htvnzp7N+/bVI7+7xcZsVun7Agp8ekntE5+XdZbhhy5dlV64OskLc\nNZydZ+OsK0eenS9OHGbmwpmuEC7X2JlQfTmhprR05iIsLPStt5kwO6kpHGn1EYjf6iAF2xloOcpK\nWyuxznOAD4FaRnEfcxlCqUuVfDa8iV0JbWxo1ggn720BVNZ5h8Ntl9hFhD3CZ/3rz82ys2ytteX6\n2bOZHwml77vdo0cKTQgazsfe81nvumZV4mbC5rzVTc4ZeqckITU28nxJCd+UlPRLwvC+QqudVquV\nxPMSV34LMd0CtnBIPN/33Eaa96EzT5WKUsZbDaY7np3Ae0lYf/YIVg9ymooKbiwooNzDjCAOKG9u\nJnf1ajYmJTH4yis1x0cQBK6IjCRahXDj888Zf+YMN69eTamHI2hCezuHDCrcwNeB2qyTO5gzrtj+\n17/LLpySJJNorr4qJ2L9b5n8v35EamZm0ELyAjEM8EdOnT3fTsr3UugZ0GO4v/yRliNGjODE/n3M\n+dH9HNnwe+zRMYjtNiYkp7Btf7niORfIxxm1dUtL3bVhzRqYM8cQOaUWHi8A4W1tQQklDyT82ozC\n7UIhRKCFEMJ3AH0lOUL4biAYCiyzIb96aggzrqLBcortTyWg2bA0T3i+oNww4waqr6qGebjGaP3x\n9eycsZPKnZWqJJrWZhn0XwgDCeE2qliTJIl2qVlWnnljHzAdpWJLAMtdsKgINjjcIp0b7q2CQOH4\n8Wx6/nmfosyEZWm9/Gvlelu27I+K/G3h4TZ6bSlQkoBCsRQBXCdAySAYEAcDe1wkDJ159Cbca2wD\nrToWAi0Yy/UmSZKp+1zvmnRoKNnU1HaR0PgfcP+7kPp1HMmx8bo5gAa8YDzk00g+qqbe4TQ0FONe\nE7IpL99JXFyc3/w47uffY9hb1rmOi2IpaeN+Q2fnDaSmztAk7SVJ0nyGMvBeyDrpo0y0X2nnf7r+\nh5vm3oalR1J8yR9XUsIxfMPVooqK+EF7u2YoqD/FgtHjTjiVxthnI6dYk6/cTgMPcgsrhRMkCiKt\nIlw2fgIJXbGcPT4Pi/1l98gMuYzWB9q4bzc+4eSWH8LIsl6fDdrUW6bydetRBn8Nw+3QIsKfi3/L\njt07+Lcpd7Bjx6cBfUDxhk/4kcbHGb21xXlsRmoqUpvNcAizGvqqEvdX/iclJSy228mJiaHEg0DJ\nsljIs9nIP3wQxiRhP98JUiRSd2BJu/UQjGduoHkUzUArbFQYO5aIl1+mWxD8qvV0x7M8Bu73zfdE\nRgbVjz9OriMflRNxwDqbjSNDh1K2a5duH06fP59r169nz+rVFHuMc4/FQqXNRjyAR0i5FcgoKODI\n44+7jQQ02mQmR58WzDrIjhgxghOV+5nz4x9xZOMG7NHRiO3tjB8xnK6UMfxx5EjsCxb0KSTPTPih\nb3X9k1M26xlsP24IqL+c9fMOvc7MymJJfj6f790JoPmccx43+3FGbd0y7fCKOjmlFh6vG6pcVWUo\nlLwv4deBhCr3J0IEWgghfAcQLJIjhEsXkiQFRYEVaF4zPYLHCIySNmYQ7Ael2bA0NSx9ainVY6t9\niCXpKolqezVPrHqCV9a+ovl7Mxto59/MjqcpxdpAjezyp4CbVY5HQuMv4N/XiUwedoVCUbYpz39o\nqz/yTPHy70DRiSJ2L5RfZj1zvTnzt319NI7BfMlwumkhnHA6gE/h3ec9FEvN0L5IDp8lDmV/GguD\n1xuLZrI0E8BvF0V64i9TkDyzZs3lpuib/CoQdce/PQtqinxzg90I/BkESUC6yi0rEutFRg5KZ89+\ntymKVg6gpgmwtUpdaaimqNLNR4VIM87zfdcEf/lxtFWcU9izR2TjxunY7avxJO3LyuazYHoa+3fs\ncG1osmbN4qabPqK01F1Gs7Qfq1pYbydI/xjMP+6/Xd54ODZ/G/fvZ2xPD9/btIkjRUUQHQ3t7UxK\nTubPH3zAG0VF/M5LDTVGSmDSpDuCQip5QltpPAIL/8Og0TOp+HKHq3+tVqtPHzZLPVgj5BBgVxiw\n+7ZwEULOe27pyqW01hzlLxY5JNJFoLfCorgaNhw+BJ1lirEw8wFFjUCfNX0We0pr5LQEOh9n9Nab\nvuZidKK/8nRKkkRkZyc3JiVRvXixnGvISThUVLCzoIDulmbEE1ZGeJCWZR+WUbWrqk9zSW/z35dy\n+/LByh90w0YrKniuqMhQ2KzWeAonE+SwaBVomYVsd8wjo6HHj1VXs86jjAeAj3Hn6XOWEgcsb27m\nyY0bObthg2LN2fS3vynaZCZHnxoCNa4YMWIEn3+4V+4fByGU8+STFCUmmso7pgazBgBq8Gt0cYVF\nIbfSyoGnVT+jBjpONDQ0sOCuuzj01VcQEwM2G1cPH87YsDCO4/VxRiUkH0yY3ARATqmFx+fZbGwu\nKOCUF5FLRTnhLxexrHK/evmKSwUv/Fr554uQdudStwnVgiAI1wEHDhw4wHXXXXexqxNCCBcUlxIL\nH0Lg8BfyGOg45+SsoqgoQyPkdzvZ2ZWmySx/SE2dQV2dc+PkDYmUlJnU1pYF9ZpmIEkSC5KT2Xz6\ntOY580eO5L36et0+j09JxPqARauZxP0xkda6liDU2A0z4ylJEsnJCzh9erNmeSNHzqe+/j0EQVBv\nj4ScR+se7TrFvB6H9Zj8RdSISsTIRizniRzWn1pPfK1EUg0M6pWT3zenQWuqwCOjH1G8/D/00HJK\nNrzJq9QzxyOX1lYEFpFMI4dxk2VPAxlA3+4J7bGwMoJr2CCcUriWbhdFHg6P4mTXn5CkO3Crh3eQ\nnr6W8vJ3NB1+jVyTuGsQsk4pibIvRcZWjyVCiOPoySPYI0HshKvHTGL7u8oQydTrUqmbV+c7nx2u\nhRvOKpWGLkWVhgvnYz75qEQeJJ1GygHPORD4muBcF/2NxaucVJA8O0SRtY66x8bKAY7JU5M5PVdl\nTfg4Bm5dATeo5PUpL2f+6tVsanM7a+4QRV4YN46xM3/Ajo920CV2MaB3AG3fSLQ0rtMc+76EMZm5\nz9V+7yRQi77WIISOi0z8YgqtZ+Jc97Ot6WNea+tSJON3okSA+8LjsHS1KssxeH8pCHQPZaZwXEAq\nvgKsh1DOIXNlq81Prflsto5O9ahRxYoakkeMoOGRR1QVHuzbR9bq1Wx2JBGXVb9yrrd5DzzEK+te\nCeh9wXPzr0hr4HGvBNqeGamplNXVaar+ZqakUFZbG1DZPuVptN2fulV1PO0Q9lYavb/boPm7pAcf\n5JuaGkcyATl9QU5UJJ8cP+ETgq513YLcXD7xINunzJ7N/j17WHzsmGKOvisI/CoigsLubgUZqTZG\nmus5cmEpJSnUHlDm+lMjUFtHjODA/PnqaqiqKrItFtbl5enOt9TMTOqchJdPXSRSVq6kdu9ev/NW\nlYjzqos/Ik5BwnmQU1SUw5/Wwh3NbtMdJzog7vU4koYk6YbCrsrJIUODnN8uilRmZyuI4oaGBtKu\nv5727Gxl7sqKCga+9BL33H03uz79lO6ICAZ0dGA/fZoX6+u50+O9Qm3dkiSJ5Ftu4fRTT/l2wOLF\n8MIL2mORm0vtJ5/49JnnHK1va+XEZVYsI2PgbAIMjIWONhhmQRjS7vN+5nsZxzNHazxfew3S09XD\nr1XG2Z8q8bPPPmPy5MkAkyVJ+kyzYgEiRKCFEEIIIVwEKEMeZxHMzZW77MdUQ377UrYa+rqZu1Dw\n90J/a0oKO3Ve6CVJIvyKKHr/o1PznLDfR9J96nxQ22l2PP2TmbdSWyuHFTz02ENs+GYDpHmd9t/A\n/ZpFcMXmKzj5/06q1DHw+Tz62tF0N55i41kvdYsAi4ZA+IgrOPm5+5pXxCfzirWB21VUXyXAfWRh\nYbOjpFZgFrAC+Rt/YPeE3likpf2GO24ex/7SUtemqDv+Mj46tAxJutOnLFPEgs41b75tHKV73Eq2\n2dNn8+H2Yw7FziyP6ynHQpIkXwLJU4HUCSP/EEN69FCF0nCxRu467xfuo19/y5nen2FBTfXX9zVB\na54nkMPrFKnOC+8NjeaG828jYP1ftDcc995LbUOD4nAJcP84OPe/cU9eR4492pQEYjA+ZJi5z7Wg\nRwiFl0bR1exJ/NoZI4Zz3LG5970iXCWG8aW926tOxsjSnCdyKGosUqpnnDgmwrvZ0Om9QTNOxKqR\nFnrzWa+c3Lxcind6qcRz+5anM3H8eCyvvGJuzgnwf2MiiBlyU0AfLcxu/o0iWB+stMr2p2Q2o6jz\nHs8BvQNoPNNN11+07/8B997L6PYGFQdtfRLBX3vU5qiYkMAvDx3iNj9j5Hc9R/7wNaTrenp6Yh1K\n6Ckc/6iYJceOKQjUTYLA/cOH+xpXVFWR+NofiI3spDeiV5NUkiSJkT/8IY2rVqk3ur2d6Mcf57Kk\nJM2QTGe/GCXi/MHloLlnj0uZeLbxOLa7z/iSZ53IOVOnociZKp4QSf9CSZSbJYqnZmby6dy5slGE\nF8R9+5iybRuVHsSimXVLs69eew2uvlrp8Oq8pgESUpIkxkweQ92sOhJ2Q1INJPbAuQHyB07LDyHl\nfZmc9YTavThl1iyKjxyRDQ08w6/37iVi40a6H35YNfzaU2moRYh6nvvFF1+ECDQ1hAi0EEII4buM\n/laJucN1PvEK+V3cLyG/wdjM9Tf6ulmQJInwy2Loffi8JrEUVhRF9zfBd8U1M55m5pYzp9vRsUcV\nKiY2ARPxJdaQlSnZI7IVG4W+zmdJkkgeFseGb2ya6pafD42h/murK6RsfHgMR3vPa764jhMi6B79\nA0XIHwiUlu7v0z1hZCxcL/9BUmaauaaRsVi3bpVcv+tSFS/Fnqo/yw8hZUcKtZ/5dyf0aZkkMWbM\nrdTVvQuRuRBd4pH8Pws680hJuVN3TdBTj+iR9mNI5TjGNjSqCiwJ2JoGv9FWoIx88EHqa2p8hJtX\nJcKXv/Q62UX+rMMzPrKvqtxgPUPUCKH48Ms4VOVN/EpMFsL5VOrVLGuyEMZnkjeBZowsHf290Zya\nf0pzbeWlFGjx/cDhLBuMh/0HS8UfjHKc+zBdwgGdOSeKDtLSaa5i/KNFf6rE+vrByhNGSbG+Kuqc\n4zkoPpHWXy1Tz/e0bx+xBatpzbH5hDynlKRw4tMTQZ1bZsbIuZ6zPwYaEyA6FtrbYLgFrrfBhsuh\npRHngz6RBfyFYtVn7juCwPM33sg34FJDWc+epmVyPdJ4N3fgTSo5661JCLe3w1NPwcKFivB4cf9+\n0jZvZvqNN7Jj3z66IyMZ0NFBU1cXthde0Oynkc88Q72fvHNafav5AeUDYBSqrt2e7z+BEMVRo0fT\n8cc/ahKCAx94gPMnT/r+Df/rjaa6q70dli5FuPdepepNhZzSuu7IySPhq0bND5yMGs7pA3I/OIk/\nrXvx+bQ0xmVlUbpvnzL8+uGH5fBrD5Jz3vTp5C1frqifEVXivy9c2K8EWigHWgghhBDCRYBZZ0Wz\nCEZeMzP4LjjFquV18E70rQdBEP4/e+ceH0V57//3TNgESDYBIyjEwAYlELFYQVHAiparSgLqOafH\nuz3tj3COId5vBYVTCRUVNOcQEe1pa1tbe1pUstyhtLSlGFBOK9pIRBLBAF4i7G4CJCH7/P6Y7GV2\nZ2ZnN5sL+rxfL17AXmaeeeZ5ntn5zuf7+dJXycZXczjadwqgRqWvkt0pfR3P+Yyn6IjT6aRqa1WU\n796Ma2awfed29qn7bBW06Oh4VhSFjOOnuM7k/ZkCHjqu98Doh7EShvYj7q8qvHVgc3D74XRkTtg9\nF4kUgOjIPgOvmZ8LH37/TioqXmf16v/D4WgiPfssBq+s46VIT6vdULwPZtw1Q7dtuyiKwvTpl7Lq\nV6Oh8JBWqCKoyqqAtZVaJdoIDh8+zM3XzubT9/eSKcCrwDmjvsGvN7wZXbXM0BvOXkXUQHDOsKAD\ngCdGxbGIimiBbWe1RTSpGaj3Q0YF9P8dNKe2BxDLbJ97M5JZXEic7Adfno9o6QupJ6htON6uPNMf\n4THRF4HP9Gb+uOhL9HiP7TEohKCh6ZjVVNECsFHn24vXW8uwYVPjUmB1twWGUbp7Y9pniY05oRBu\n4GTXd9RO9dxY1UmtCjcky3cunmIEHfVdCxzLhUPO55Nly/gkolKmunMn5y1fzvFhTaGNAzRD1u8h\n9b1DzM7NTYqPXOBBUTznaPpV01n129/B/3sAxoVVD616C15eBk0BNan27bN41/Sae6MQvFhfT1Wt\n9gDlnkfuYcXBtzSLhU3hD1v8vH/e+xRe/S16fekJBjhTPR5UI9P53/wG/vmf9WooRcF/0UV88Mor\nfJCdDWFeZ8ybZz0vbFZ/jOxbsPA0NPOARfNHq3RXUk45dgrohBv9+/1+zfPMwo+Mvn1NHx7FOk6z\n4hrqe++R368fVx87xkYb3oBG++11qJGVX6ALtipov82e+xwe9H3B1GHDguc/JTMzmDIf/vkZfj+i\npoaq5mbDFF6rqsWB1+xUib3zppssj6mjyACaRCKRdDHJvLG2Q1fcLJwJlWKdTierd+5k2YIFLI+Q\nw6+2mcZzy423supXrwGHQhUeA6laa3O59VYL47AkYSfYEk/REbPKp0FlSoyCFsbjOfwnZWg8m7Vf\nCME5qb1RWpqi3qN9S+ekpgXbpygKLX17I3zNpj9cW/r2Nu2rZKUNhb9mdFPs9R4n+qY/1Eo7xQvi\nabv52uIDbgLup63tP6mvb1cg1M3klxj/KH7RAzvNs5Vj0+e4VuEyXMWo0B58/lh7P4zDhw8zMW84\nK1pO6IN57+5mYt5wdtR+qAuiGQftzSui+oBngI+OHuWGIUOCN7mbV29maflS3TjPGpTD3jgqotHe\n1uMpYTtuBn4NWWmQfbqN/i2HOaZCw9D/xlO/hZSUczq0NiejuJBx9WQ/cC1GY7aBW1jHKsPiEmuB\nBm6Net3OAxRFUTh1vNVqqmjqRd2bPmA6Pt9T+HyB9uqLC8TyF7RLLM+oeIIlZhWrybgd3npLX/mx\nHcsxFwxahjrP7kOLeG7+w9tvlJalgK5ox6XTp/PsiBGICE8vuw+sAsQTFEtGoSCA3252M951Adct\nWcJ7YZUyL/J42N27Ce/UsA+3+0Vqypw2lPr6pFUbjfscOZzwvQf03o2KAleMB/8DsOQYtIS+bedh\nQ2Dsr9m0hnOPiCgF0m93wYPvwENtfw++7gemAp8uW0Z1RBCSd96Bu+6K3uFvfgN33BEVWGPsWKiq\nMvbG2r3bsvpjzIeNRg9Q/GhiTouOaVVbEwoUq6oKTU2WAUFOnIhZWMcMq+IaizdujFnkyQwhBNkt\nGAZbfcD/AC+eauW6dqWkAK7EyHFWI3wuxvqNFul1FlAlWgUhA0UROhUhxBn5BxgDiHfeeUdIJBLJ\nmYbLNVmAX2hXzMg/fuFyTe7uJsaN1+sVpaULhcs1ReTkFAmXa4ooLV0ovF5vdzfNEL/fH/d3vF6v\nGDnyGkHvIkF/l2BQjvZ37yIxcuQ1PfJYEzlOu9sIvK6NZ48gbZ6+X9LmCfhEOJ3fEC7X5PZxMVnM\nm/dEVF9dM2SI8BtPCOEHcc2QIbrPP1pcLNwmn68E8djcuR06Zq/XK+Y9NE+4LnGJnEtzhOsSl5j3\n0DzDc+z1esWoUVOFqm4Im9d+AXcKWGs4z1V1vSgtXdihNhphvLY8IWBDVBuG4bLs8ykuV+LtuMQl\nWIhgUfufiH+7xui3feVFY8Rai/P5rYvG6j4f6vP1uj7vR1HUuPCCmApiXftxBY5vg6qKqaNGBc9p\nYDzX19eLtMFDBWU/EmzbJvjDH7S/y5aIIdnZwmvURgWRdXnYMU5EDMpCrI3Yp1tBDMpEXHSp/ngi\niXfeJjLP5817on3MRh6O2fXJKwZRICqjjkkRrtR0oSi/050LVV0vRo2aGnNd9Pv9Ij07T3CzGuq/\n8D83I0grjJhbd5jMLa/oR5H4pjNLFOXkiMkul3hinvG8tcLr9Yp5854QLtdkMXhwoXC5Jovi4kfE\n1fn5Ued0raKIyQUFwuv1xlwrzfvcK8geI5QlS3RjTlliPuZeAzGQi8QwXGIsOWIYLpHFPAFekZNT\nFHNMPDFvntigqoZzbr2qioWlpVF9MrmgQHf8HhBXED3ON6iquGbkSPHY3LliisslinJyxBSXSyws\nLY3rXEx22Vuj/H6/KMrJMfxc4E9RTo6teeL1ekX+2HyRNQJxfj/EJRna31nZCP5ZPzazxmG6bhn1\nYbzEc45cEyaExk7kn23bBIMnxrX+Tw7r25yB6YbH+UT7uhr5+uT2sVGani5cgweLnPx8MXTQIJE+\nYoRx+8aMMW77unWCsWMFEfNCXbpUjLrqqqix5PV6xRPz5onJ7WNH+GPUAAAgAElEQVQu1vz3er2i\n9OFS4RrTfp0f4xJOl1N/vVoUce26xKX7/tRRo8R6VdWN//UR15YAl02YINQlSwz7QC0rE+MmTuzQ\neAmnI7/9vF6vmPfYY8I1YYLIueYa0Sc3V8xLT49ah54AscFg7BRZzEO7c9Hr9YpRV10l1KVL9dfh\nUaMsx7lrwgTxzjvvCEAAY4RIfhxKKtAkEomkGzgTUh7jpavTRu1i1pZE2ud0Otm1a0276uMELS19\nSM06SdHtl3Sav1xHSbaK0UhplZ4uwGmSruf+MT7fz/H5bsJIJRLos2/NmsXGigpTs+SrZs/WvfaD\nZ57hhj/9CT74QFf5cp2iUD5yJG88/XTCxxvwhqseXg1FwWazYv8Ktk7ZStXWKt25nj//2XZFiV4N\nBf8NTENRBEJEFy/oDGWm8dqyA60SaTj2FQgQ3zgSQtCa0gotWmpTlL/aZP1TfICj//i7eQov8MA/\n/qZ7zUyBNWPGpTy//UNSwpQvzwD3on+CbqRiCbTlqadW0XJkOSx5B7Ieh4xUaGwBTy+am/rwR1Rm\nEl5tVKE4U+D5dmj7We/Cyz5jdd8qH9xdty/qODtSyTaReW6e7jsR2IimRAvHyVHlSZaNfpr/8nym\nU/HueOQRli59icrKF+NWwymKQnb6EJrcfYHqaHWvewQZjo84e9C04LYbGo7h80WOGB+DGM/LVHOd\nz4/i8xiqgWJdn3w+H+PGzeLoB07O4iMG0coxHLyxaj8/4eOoc3qVELxWXc3VgwdzXlZWUJVW/Oij\nrHrqKZ1aq6bhNH7/AwZ7dULDH8j47yvIXrcuqB6ZMWEC1dnZbP/yS90697/AQ6TyE/4RUYW4gjls\nIyXl7JhjIl5bgyUPPcR91dW6418GLESvNtGlak2bxpba+H0UQVtH4klhTERRZ8T8J+ezv2A//gvA\nE/iygqYq/QUoDiXoGZq9z1iZA3qlTaK/ieyeIyEErWlp1umBGalhBwMNFLKOCma2F1wJ77tw9ZSV\nxYLRlQW0FWQHUN7URHlTU3DbeYpCkxD6dgoBvXsbt71vX/jhD0l/4AEGhM0Lo/TDeNJ9Axgp8Esf\nLtWndoZ1jPqRStHUIt337WQ2BLb95m9/S/5ll3FSiKj04D4VFbyxe7dBbyZGor/9dCb9Yem0FW+9\nxbZly9jZ0BAsiWN0/hXAyGAhgN25OP9HP9LaEK4E76AqMWl0RlSuK/4gFWgSieQMxkw9YfeJvcSa\ncPWAleqpoyRD3XUmYaq06n2d4BaTJ7Y3q4K00qiHkJEKrHif5Aa+s7C0tEMKByOK7y22OB7E3Pv0\n6jZrRamnXYHXNcrM6LXFL6DIsG2xFAjfzHTaUuBF4vf7xZDRQ8SgASYKrAGIIaNDisK2tjYxVrF+\nYj1WRbS1tVnuM7wPwsfFqJSUuJR20eezrf1vTWmZRak4H5cYQ444H5fIYq4gfaSmlFqo/RnWC8t9\n5qemRLXZaG6p6oZOuSb4/X6Rk2M8LsArYKoAt+X1KZbaKh7mzXtCKMpqba3QqVhLhaL8LrhW+P1+\n07ZnMU+sxVits05VxaTR42xdE4qLHxGDGSrWol+LxhN9TgPqxvUR43y1oojhaWlR65kbxCBGtfdx\ndFMDyjGr8TzF5RKjss8Ra1EMj7USVUy6eJytfo9nDf2mMyvq+Ccb9InV3IqXWAq0yWHbj1dRZ0aU\nejb8z6MIx4BU0WtAb6HkpImxqvma5QVxSXq6bTWUGXbPUWwF2oSoeX4uuWJmRkZQJeYaPFgUZWSI\na0aO1M3zqzLSDfvfTGkUmBfuiHlRlJGhqcnsKtDCVEVCCMtrQLLOv9frFSMvGyn6jUAMy0KMdWp/\n9xuBGHnZSMvzFzlvI1XsxfcUi2Gjh4nU89JFr/MGC8eIfNHrvMEi9bx0ccE3L+gRv/3nPfaYpvoy\nUcmVpqfHPP9GyjSjc2F1DTEdzzZUiZ2tQJNVOCUSiaSb6OpKmV8X9B4z0wmpfuxXJ5MYY1r5r38e\nlNaZP240rKAXXYkwnpLtUbsRyVM9Zrr64bvLY3o8zp/1w1t3LLhfs4qQARKpFNgRIteWo0c/oq1t\nL5EHlEUpvwxTIITjBu4YAcf/laAaKLLiWuQ+w9VTLQ2/56enTKqqAsvGXMwf39FUZUIIhjtUPmwz\nH0LDU+DDVr+t/gtvS3NzH3I/20JVm7mhW3iltND5/CVZzCcbN/3bFUgNKHj4OwSfvwtCLfaRnn0x\nA4YKWpQWBv3fYd42tmMC4HJHCm81twaPx25VzWSOc+sqsV6czivJzj4nKdenWO0Ordv36fogoNaM\nXLeN2h6rAutwzuEjQlUIza4JQzJzWek7zPVh80IAs4HIWb4QGE+0389C4HKM1UluVG6nBA+Rflyx\nK1YH+vHbQ4fy+4MHTY91ytChbK2tTag6odl7Vzj66OaRWZ+EE1mFMF7iqZ4dUCDdZ6bWsqFAFEKQ\nOy6X+pnmlRVZlQ1HPgMUhjHMcMwFXCfvQe8ZZrciqBlWbbeqTsjOnbDkfWj8RbA1ivI6jkH30zLv\n3zXvsXalkVJVxch166havz7YX5NdLsPxNgUwX0HgSqeTc7Kzg9fzS2fMYM1777GvsFBndM9TT8HV\nVxt7AFZVcdF6N15fPa0prTjaHBROKaTscb3vYLKqyvp8Pm64/HLuq67Wnbv1isJzI0fyRlVVzHPn\n8/kYP2081RdU6woxsQa4kJA3aMBzDWAfzD13LiuXr4zZxs4gMLbyJk6kLqA8i/4Qrttuo/bw4aDX\n2V8wd10tRVNhh8/FZ/LzuXzSJJ1nYqRit29LC5uzsmh+4QXjxp44oakSs7MNK3bu2bNHVuGUSCSS\nryI9NeXxTMcsnc5udbKvGskcW8YpX0KrkGeVZ2NYQS+6WIbT6dRuhhJIeUnWMQohONF2yvJ4TrSd\nDLbPvCJkcIsJFQvoCJFryz33LDJMGffwKHP4MatojkhJhOIsOH4j4bUg8J/vp1pUs2DxAsqXhm7+\njYzRhzGU6zAuCjETeL4hVERAURS8fVJZ19TCTIPnumsV8PZJjVlAQVEUw7b0IQ9hEVgJTydRFIWU\nFE8oFVCXHgdzGM8RdqIF0cK3mMEA5zBq39mKEIIx/bIQXvOKlS19+uqOx7qS7UTe+Gkx71e+kpBx\nvRnWVgI7+O53b+xQ0M6O4X5g2/EWRYhue+yU5CzdbY/xNUEIQZ8TDVwXEVQ2S0syS2Ezex1gJn7O\nprI9gBbaol37BiEEzrY2w2P1AfPT09np95M7eTKO5mYKJ02i7LHHYpqIxzrHx1F1x5+sVC0r7KQw\nho8hs3S6nz3yiK30aEVRcLQ5rA/qlJNA1CMyDTLAs9hLG48Xq758tKSEn1x2GSfvvtswPfA7//Id\ntm0LpUFn5fjZW3Q3RKTIiSuuYJ+iMOXaa3HW15Pe2srnHg/rIFhAJNA9E4ENGAeKd6gqN373uywq\nL9dVlvyBzxdldD/jiivYvn49+1JS9BUkd+3CseK/2DvxCOIaEYzEVByoYNu0bcGHOUJ0vKpsgGfn\nz+fBffui0pKvFwJ13z5b527+k/O14NkFYeNCQcsJHh72wfB6Afnw6s9eizuA1pHfeImY9B/JyqII\nOJmaSkZWFhv37o2y3nACxYrCitGjKfd4dAFUdft2Jr38MkvC5vMbK1Zw9UsvUd7aGky/zQPqhDBu\nS58+DDjrLGr/8hfTqqWdiQygSSQSSQ9ABs+Sh/WNaOzqZF8FfD4f85+cj3ur2/KJbTwIYVbhUdEq\n5FnecERW0NPesAosdeucOKXGOB79j7We7GmoKIpplVx4jCO8wu38hbOpJItWPDj4IrUBz7/7IC16\ne/7z/VS6KykPU89EB60F/TG+wad97xmnTxPIglAUhZl33MqcV3/KKq/mExYM5ilQnAmFt90WtR2j\ncZ7pGMA//vEoQoTOhdlNLkRXSgNw9TvBwwf/wfWEonkK2s3jKqq5nQVR6qHw86woCjNuvoV1q8wr\nVl57S6hipfncAs3XawIrfYe4zhemZElClT+71ZMT8a5qbGw09SOatWWLoQLhwbIy2w+VjNpuVoGV\n9n0fJ3odMrom9GsPmkYyEdhESG0mAKOzZvZ6AC2YdxT6uaDPaW19PDmafJePxYuj9VxG3nj9vI1R\nx+oDxmdnU/3AA/ivuIL6gHfR7t1sve46rho7ik1/2pTQNUFRFE72zWad77BuHkX2SThGcytezIJi\nl86YwVghuGH06KgxFPkQxqzyqZEXJ0DhlEK9B1Y4NSqcCB2ThzLmsI1VVOseQmzFPIAaT0XQeFj1\n1FP8/MgRti9ZQmVY9dAij4erTpxgb0YbtbVbdEoj/2WXGW7LP24cH//Xf3Hk8GEUNDXZFGBVerqu\nMulIj5f/aTrFi0qbzqNvo6qybMQILmjuQ17elKigZXlZmRY+DpvnPoPAWmYKWvCsIOzJisHDnGR6\n4CWjmqt7qxt/UcQ2BJBq0kCIejhnRTJ+45l5nTFvnva3iQJtUP/+rHn//eDcumn8eDAIcK8qKGD1\nn/+sU30uLC3VgpMRVXX/LgTPNzfrXDenezysMqlMzFtvke33MyUvL6kPlewiUzglEolE8pUhnnS6\nr2rQ0ix1wCr9zi6mKV9ppXBjBYww+NG5T4XXS6A5MuAQSkvraWQOzMU35bDp8Ti3Dsb72aHgS9Hp\nZ/pARE9IGzZKGdeM2HcTOp/tvwkH5UKxeQpTztocDu0KpWUlkk43JtPJ8fOzgz/+p181nd//6fd8\n0bSf7M8gqw08KdAwEAY683n7D29HGUYbpsh8CFSOgsaASgwC5vKRN7mRqV0BYqXHRacCRp/nQBrQ\nvQZFLp4PSwMK3syazK0sSnmVCl06YYDIFLZESJaVQKTarNbr5Uc+X1QKrw+YBjyOVqKgI6ltkW1X\nvf/HysZPuN7g3sY8bTL6mnBJZj/2+DymaUnz0IKpCuYpbFapbQK4IB0OPBjqAGW/wsgPR0YVKDGz\nJOjHbH5BpS5AW5qeTsX8+Zr6KJKdO2H1EpjZaHpNMLtxD7w+d+6juFe9xoscCs4jLzAd+EFYn1jN\nrY4SGZydHh6cNRlDdtOjA5iuLTWAO3JtAfCRxQLOSXmZkeeeRVOvXrR98QV/aDJW4ELHU1uNiExh\nDA8mRaYwCiHInTyZ+ieeMN1eTnExh2pqUNDG/uXtwVmuuCIUbHmrCpa5yWn+mIKzHcEA52UzZvDG\nH/dRU/NwQlYawXVxTB51RXWmE8nldlH7jnZM8aT7Wu13dm4ua+rNr3+xzp1lGvArwB2YHk9KRR9a\nP7NWrCfrN55pyu9PfwoFBcYm/bt2UeLxUF5WpmuPXesNszRbo/XyUeC17GwO3X9/lKIybflyft7Q\nQKg0lX7+f/jhh52awtm1ejeJRCKRSDoRfTqdEV2fTtfV6FIHwnJt/Of7qb5Ae2KbKIWFE1HVTdFv\nNJfB2lyUGiXU9QLU/SppW/qgtFxF+BuquqFd4WJUja77ueXGW2Ftrhb8Czse9qmwNpdbb9KroQLp\nZyUlVbhc08jJmYXLNY2SkqoeETwLtLG8fBG1tVs4dOhNDhzYTGZmDpFptTpFoRECHG2hJ/lm6ilN\n9WX8M3MtUDfIR11RHfUz66krquPlL1+mV69e/Ov1c2kb5uJo/mDahrm4Y3ZpVPAMzMc5+UBhNaSF\nj3MnR9jJ7ZQwMqUPs3JymOZyUVVSEnWzbZUeF9hFTvoJhg6danmenU4nb1RV8fa8eUxzuYL7fHve\nPH6+dSvzn5xP3pg8csflkjcmj8yBXhTljaj9ZeOOSicMMMPvZ0dlpUlL7RE5Lmprt1Beviju4NlN\n48czvqKCLXV1rKmvZ6DPZ5jW9SzwBCFfKAiltt3XntqWaNvfr3+f8gsvZIOq6qatGyimAA+LDbYS\nfU2Yccu/ss5of8D3gO+Tx3BcjCWH/TgNPxtIbTNiLdBwEboOEMMF+/L3Ra3PenVn6AvH+SXFDGWt\nogSP1Z2Vhd/gphfQboZPZRpeE66cOoW8vCnk5s4mL28KpaULOXz4MAtLS5mSl8fs3Fym5OXRn+Ok\nDx/CHcwMHv8YXFRzHff0y2HK0KGWcysezAQeiqLw7Pz53B+meGk/HNMxpKnSpxtuT1Mg7tC95nQ6\n2bl5JyWDS3C5XeSszcHlduHceh40/hV98AzAiYfnacmdwJuHDrG1ro6UAQOsltAOp7ZGbVMI+jQ3\nR63m4f/u3dysU/06mpu1IJjxBnE0Nga3MT89nX0PPKCpgQLtVhQYfwXcP4vj6Wex+cAB3jx0iC21\ntTQ6BrYHz/TjVkubvo8FC5ZZHk/Aj7I1xdoeIlDNGbR03+UFBVHzf0N7MPeBsIqlVvsNKNkMu4XY\n506XBhzJEGC/yRdrVPoq2bGrUybpN557+3ZjBeJ3vgO/+50WdA/0VXs6bcG6dSx+9FHdxwPWG1tq\na4Pnf1F5edTcN0uzNVPsvg2829BAyZIluG67jZziYly33calS5bwi4YG/omOX0MSRaZwSiQSieQr\nRU9Op+sKDFMH2jFKv4sH85Svv5CfM4yrz7mWje6NtKqtOPwOiqYU8cjfH2Hp0peorHwxpq9RT+GZ\nZ+azffsuPnjjYujzrubh1p5mNdLl4+mnfxD1nTPJ0zDQNlPvthOFUGOsKFQ/UimaGkphMvaAE6ap\nTesUheJMYeivViNqmOaYRu07tTH70Gqck++HvpURqkftJrd/7vu8eWCLZepwrFQgx4Bs6mq3xmyj\nkaefTj1QFK4eOEjqgTtoaRAIEegcP/0x9lGD+Hx97JDoNsIDGmCdwmjlDdaR1DYrD6zWzIEc3fsI\niOj1JvyaEOjHHzzzDDf86U9goB58MT+fG6+5gY0b3+ZoSx969fLxWOP7qMcbuDZMDTVaUbg3NRVa\nW3WvrwWKB4Dn29HHYLQ+m1sSODnMu/xHxkWMyE6hT0sLh7OyLL2L6J0RNd395/t5d/3H8GVIUbli\nxRu4Vw1nRcsJFgVfhfUvvcRbw4czee5ENm48wdGWPqSmnuTOostYvPg1Wyo2K+x45kF8KXbW6dEA\n0V6c0L6eLy2nnNDc1ZRsf7X122JiYSGbTNRQyUhtjToKReGTxhOW69YnjSeCgSlFUSicNImK3bsN\niw6oO3dS5PEE/28ZnB1/Gc2rXorD09GelYYdP7rwhzmxPPDsjC1IzrkzTQOeAPwC8CuQH+ZVUNP+\ncO7Wm2Nue82WNfhnmf/GW7Nmjc6j1AghBK1pacbrRd++8MMfaib969bpTfrXrrX83RYrsGh0bVWI\n9lIMXEMygfKmJsqbmoLvTwFuNNlHYP4X3XmnaTuSQdIDaIqifAt4CBgLDAJmCyFMH48pijIJ+EPE\nywIYJIT4LNntk0gkEslXG7u+Pl9F4nlim8jNsrXR9xpTk+ozJbAUwOl0smvXmvbjPEFLSx9Ss05S\ndPsltlLbzoRjBItgc3MZrK1EUQ4ihod+5KsfqRTsL2DxC6En+YqiUFg4kRUr3kCk/hH6uoMBxyNN\n07mjZSh5zr+Sm5nOCYeDfY0NHPl+bH+1WAUDYo1zo8IVgZtcq9QbRVFs30AlUuTCzFzaf76f1hkn\nGf3h03g+DQWb2xpOI3wd9/XpTCIDGkY3RGDPGyxWQDDhoOX4m6iu7hN1TcjPf4ZmNZ+8MXk6L6Gf\nb93KS0uXUh5xI14ZlpYUvv1lCxbwXMRn//jII7y0dKnu9eoTn3Pke02G4z9yfY4d/MnEn3kJmw9o\nFX6zRhXQYuFdxMnG6E0pQJq+uEKm2MyKlhO69FsFzUTdX1PDzm8f13lp6TYX9n8j7zYj4/7AZwOV\nDxcFzxCsX7GCG7ZuDaY8+/1+22bxgfZ0tMhL4D2z3xaK8jr9+v2QN9/MZvXq2TgcTUyffinPjhiB\naPd7ChxPePEDSO41sQEn6/AZej3+LwpfnGrTeUaNvuYaev3iFVr+4264IpQix86dFCxfzuL2FFQB\ntGZkWAZn07L7xTFujYOWRlj50UU+zAHz+W/mx2jkIxlP4Qozyh4vY9u0bVSLiDTLQyq9TvSm5Y2r\noc8/bD2cC0cIQUPTMctF9IumL2O2T6dAjGHSn8wxanZtjSxGYXQNCZwHu9eQzqQzFGjpwN+A/wFe\nt/kdgSa69wVfkMEziUQikSRAvNXcvkrE+8Q2EeworXpkYYA4OZMUZYmSkKJwaXQ1u2uu+QaOs+6g\nZfoJCAu4UfMyJ7f0Ye3faxg0aBAAueNyobfPuEE2A7z2KuWd1r0QHkCPNK6OPB67N7+JEEsh6vnH\nZ9TWVulMl7tSyRIvZmk5RubyZoG14LYAX0pK1Lm3q0yKJFyZYnRNmDHjUrbvOcrLX2zXqQErDlSw\n7Satwt8ii4rA4a99Kfqxn/NpEX1J5QQFop/uZj5QKS5vTB6kmnhjRazP8QZ/xAkPmJlu79wJAz3R\nrwuiirxk8yvD9FvQfM4W/vpVlqxcGdunKQ7j/iUPPcR91dXGQbvqaq6bcA2fNPajtTWdjKMNlmPo\noLeRYcOmBudzZmYKqroRv//aqM/Ho0o3GkcpKV4aG49x/PhTfPllaA19+eVN5Ofv4s9zJrF848bo\niqCdUOTndMZo5viyolS//4vCQ6TyYmsj19U1hoKTP/sZv3YKjm5eAq9maQrFU42kHvbwxLGmYKKq\nAjgaG82DLUKQnZbYuE04EBXxMMeKSIVs4JjMKqKaKdkumzGDYSKL0aNviBkQDqQBL1i8gEp3pf4a\nujegym9J6OHcqeOt0XKtsH+fOt5q6/eKpQJx926Krr465jYiiXU+zYKTRordCURXeLVzDemKh0qd\nWkRAURQ/9hRo24D+QghvHNuWRQQkEolEEpOvavDDjNKHS6k4avLEdr9KyeCSmPJ+ydcHOybyxtXs\nQsbQ9J4NN1Zqj0IjiBxzMU2hK13U7qmN2e5Y4/wbH16K59NMXbBE9D7Gpu2hKoTTJ01n+8YaQ6Pr\n/PynueHqEeyOuPk1Mka2i6W5dDuRBRoC6on7zNQQSTZpTwQjY+iA4f696IsF3AF8Bwyrk7qBZWMu\n5o/v/C20nTD1iB3DeDsEU/IeLqXiSIVeDdiO3bXSbE4ExtCkSZezadPuUDBnoJf3Rrxje322a4Av\nhCBnYAYO0YdPDEy3z1u+nON5DXgjOz6qyItgrOLgbdFmesyXO1J4q9n6Jj1e436zwg1ai/SFO7Io\n5ZcmVXXdwB3M4jhvEFKIvUFq6qO0tj7fHkTTq9IT9akUQnDPPYtsn5+oFO5OKfLzOlk8rquq7COL\nn7DXsBCJW4Hbx4HnWkJRiS0w6D10FZGtClSoVVWUeL06Y3mr868oq7lq9NP08nxmKyDu8/m0QNRW\nfSBq8YLotdiwYm3D25ZjK7y4ghGBwhVm8zyeogjJeN054Hyarqkj66Aguwb6t8GxFGjIB88QhfQ/\nuPB9/hFg/dBSV4XzsstC68Xu3Yxwu7lq1EQ2bXrblno0ltI08qGVUdGBOe2K3cDr3pQUjjU2suT4\ncV0a/F3Av0BUgRoIFYsouvPOTi0i0FMCaH8A6oDewHvAIiHEX2NsWwbQJBKJRCKJwPQHevsT2478\nQJd0Hd0R+I21T9Obov55UFpnHhQLq5SWrACv3XEevPkx+KyyX0FUDgHfXiKNwY1ufpNBIgHEeKqc\ndQdm1e98wN3AW6ngTNOqqn5+GtJ7w6qG0M25ANYqUHw2OAYP4eO/fRxz29DxKqTxVPgzwzxQYFxv\nVFHeIDX7DlpnnNTNAbP1OZ4KvyPTerGrpY3H09OpzMqiNSMDR2MjRR4PTzY1MSYdPgqr/GlcVVIw\nTHWw329cSEMAI1NT+OCUdQDNtGJz+1ZcrmnU1m7R/icEVzj6UNXWbLq9seSwh0Dl40bDqrrrFIU5\nYghHiJ7PirKa0aNfxuNp61C12USPM5lBWzOix6IWEYtVEXl4P/jo3rAXm4FfQ1YqnN1eEfmYCh/3\nzcY/T1+FU929m4J169gZ4Y1lNm4V5XWGpt7JC60ndQ8EIgPiiXjpGQez/YxlIG/TYNpvgaqaYB5w\nijcgnAg+ny+oTGxRW0j1pxoqE3Nzr6St/m1eFs3BYiwCWAd8n1Qc6dmMGJBmPzj51FNUbt8e9Dqb\nMWECf3S/bauCarwPEKwCa+FEpseHX/sunTGD3du384CZQrwLqnD2hABaPjAJrdhCGvD/gNuBcUKI\nv1l8TwbQJBKJRCIxIJ4ntpKeQ/gP6GSl9iQT45tFAYNyodieqiqZAV6749zqpjVagRM6rvCbfCMS\nCax1NIDYEZP2zsJMJRcIih35PpDa/uHXgBshaxucvU+7OfekwBcjNGP9nC16BZ6Rui2AHfWIEYF7\nn3jVgEaYB1AWAlegBc8i+SUXnPMgKce+IFMIvIrCuRddxK/c6xk8eHDUp+2qRK/OdLK9MZQeGpnm\nND61F0dG5XA65TQOv4NMx0D27nqkvWhFiKzUTH7Z6mOmwS2iW4G7s50c/Nw8aUgIQW7ubOrr15h+\nJidnFocOvRlM4xvpSOeDtpOm5/kCnBzonx3yjGqaTlaLwrm9fsaIc7I1f8WG0xzyvY9mPR69lchg\nVkeJfZw+0tMnMWDAWcEAQoN4G99dng4Fbc0wDlrFDiCNdcKe+9G36RQ4X3WSPSCbFqWFVJHKjG/N\ngFQnG//6V72x/KOPmgdnIsbt0Cwvj+x9m2sNAuKrFYWXRo+mzeOJK1U7gFmQyyqA6AWudDoZmJ1t\nuc94AsKJ4PP5GDd5HEe9H3DWUejv14KWX54L52aOZNfvdwXbM+nicTz87ttcH1HmMxCyXwC6wJqV\nWjdcPdbc3Ie0tJNkZqbw3nv3mqQ864OF8T5AsKvYM8KOii3wUGnPnj1f7QCayff+CHwshDAtoSAD\naBKJRCKRxOZMTWE9U9udKJ2Z2pMMLG8WYynQIlRVnRHgtRovsZRG/JcLjkXftIbf5Ie3vSNBzmQH\nEHtKwPXw4cPcUngtR9/7B5nCz7E2P59fCp7J6A3zX0HL49NKsOgAACAASURBVDTx7wkfK0IIZufm\nsqbePMgVUI/YqfAY2VcNxxrw3WleoSFWOrF1AGUKYHTD7WMQ43mZ923f5Ebu0yyAOtnl4vcHD5oO\n88lDhrDt448NUrL1KiHSpjMobQurfAYqwUy49rZ/439W/I9pG8FOwGEqtbVbg68MyczlBd9h07TM\n2/PBc3OoidSo4C5gkHMon3ziRlGUuIJ2ycL8OANJzPcQCmf4YdBAKDYPZtkJ2lphFLTq17DbMoXx\ngn5w4F796+HBfKMxl2hKollA3Ki3BLBeUXhu5MhgEQnLdd7kXJil/BqHeIzVcB0dW7F+z8y9dy7u\nn63iJY/++Ne1z7miu+ay8vmVAHx76FDDeW4VsjdS6/p8PsaNm8UHdU59tfETp6B5H7EC0ZDYA4Rk\nKfaCLTLo284OoHVGEYFksAvNfzQm9913H1lZWbrXbr75Zm6+OXYZWIlEIpFIvur0pCBUrB+R8VRt\n+6phVZ2xWlSzYPGCbvWuszSGPlEINRUwwn6ltPKl5ZRjbtCeSPuMSLRiZ7jRdQBd8CvSdH7aNlvB\nLytz6cUv2A8gJqMtycLn8zHtpmlUX1iNv7B9DPwByCW62uQQYD8wvP3/YV0eOVYURcGXkmKr6EDM\n1C6DvmIN8CHG3n0G4zYS8zlhXisui/m8TLRZvpmhudE+w48rPCionvCyXlG43kAcsUFVuWr2bN02\nzIorZGT4ea8ul9uHHwqm8HlS4IuB4DmcS2rbQMt+AYsKvxgb9193y60Ur3qNFzmkS8tcCxRngecm\nQt2p0L7WVNO41YOqqgAdrraZCObH+SyaA2C4BboKp5wgGkwHdGcU+bEqRLIW+PIcQt1mYNAfq4CG\nnet2YI6aVVB9Frif6KIj1wtBY3U1N06YgGhsNFWJWVX+9FDGHLaxiveZGTpMSgiptcL3GTkXE63k\nGk/xk/Wv/oqXPEStCzMFvOiFu3/1Kjy/UvNAazNOr94BLDJ4nfZjWl5ZCWFry0MPlfFB/QG48RAM\nD1sXawD3hIjU7lCrAhVUAYtqq+at8ftnUFm5nAQz76N47bXX+PWvf617zeMxKJiSRHqqAm0z4BVC\n/JPFZ6QCTSKRSCSSHo5dlYyVl0aikv8ziWT4MXU2lukazm+gFB5EhFXh7Cm+e4ko0IyekneGf1Gi\nAcTO9FJKSluagd+giRCGE7o5+wekbk/l9LTTthR4k8ZezEN73jUtOnD/udmcHuS0XFtM+6oZ+AXw\nLbQgWntblA8VRu4fSdXWqpjj1nxOGCvQYvlR2U1JNVQynoLBK+FFD7pAwTpF4fkwFY8ZgbEYMKMn\n7XHoWwlpLdCcCieKoPlJXK6bYqarxePdFvj8uHGzOPqBk2zeDRrgf5H6CZ77T2su2QYd5vxZPzy1\nX2r+Yl3gU2X3OOFK4C9ELTppc+HGVTDCYGP7YO65c1m5fKXp/uJRg4W30awQybIRIxg+bRIb/7wx\nITVwvNdtM/WUuV7TWJlmpNi0Vj16yXWOYkR2r2DK37GGBnb7fLbmYrxjK57iJ0IIRvZ28EGLPd9B\nIxWfAGajPRMwI1KtmzkwF9/Uw5Afr7VBSD1qausQozWdoQYNp7MVaGqyN6goSrqiKBcrivLN9peG\ntf8/t/39HymK8krY5+9RFKVIUZTzFUUZpSjK88A1wIpkt00ikUgkEknXEbjJqzhSQV1RHfUz66kr\nqqPiaAXjp43H5/MFPzt//rPtP8IDNyEACn7/DKqr72PBgmXdcgxdgR2VVKvaSmc+9LRDWdmDFBQs\nR1U3QNB/RaCqf2FkzjCKzynG5XaRszYHl9tFyeCSbg+eARROKUQ9YPKTtwY4ORr98WygoOA5Fi9+\nQPdR91a3oXcZaErByq1xPS8G4leIBsZAZ7Ql1j7jaksaWrnNemBFL1iVowUq3bPIdY7lwg8uodcL\nvVF/3JteL/Tmog8vZfPqzVFjpe70ceYM0Ly3QmdI+3+xA/Z/qyHm2mLaV2nAbcD6Plrb2tsoXi9C\neM+11TdmcwJygPWRPUZ/jBU4oE3/vq325rlOsRrYYG84/B9auuNwnIwlh+G4uF0UUS9iH09AJaSp\nSjK1m+djtXD0E+3v5nIgU6dAiSTwekDdVlJShcs1jZycWbhc0ygpqdIFVcI/v2vXGu4ovYQ21wUc\nHTyG00PP5/SQ3sbBs/YOO9F2gvPOm0Ve3hRaWpoZMeJZg/XJeD4nA6PjHDp0KunpqRgu6M39wD1U\nC1CED5d9KqwdCif7RX3F5/NR+nApeWPyyB2XS96YPObeN5e5cx8lL28KubmzycubQmnpQt24D2/j\n6p07qSopYZrLxaycHKa5XFSVlPBGVRUrn19J7Tu1HNp1iNp3ailfWm57zY73ut12dj/WRWzDXK8Z\nUqZdr9u6pqi6r10lFqCwcCKqusmwnaq6gxu++z221Nby5qFDbD5wgJzMTNtz0fzaZzy2np0/n/vD\nApZW7Qbo57e8/NMvbLpNLCxkk6pGfSagkTMiXK0L2rw7IRo05ZkR+X4teB5BpHrUuM9jt6Yz1KBd\nSdIVaGFVNSM3/IoQ4t8URfkpMFQI8e32zz8EzAEGAyeAd4H/FEL8KcZ+pAJNIpFIviJ83fyuvi7E\no5LpbJPenk4i1Rm7A7uG5j1pPlv5jo2oGcGkMbPYuPFty+p8QoikmM4n2v7wFKlevRr5InU3TbdG\n3ywnqy1mytFH732Up55aFVdbWJUDRw6iPbePdB7SMFKsBPt8an100YG+4LkSuDB6d5H+TbHOm9a+\nQIVHpb099quwGs2JGTMuZfv23ezb94BOmXQ+g/iQT02VJlNdLrbaUKDZU1UeMDyemNuO07/MTgpf\npAG43c/bV4+GKv9dffUVbNy4O6nVNu2iV/EZ9eEUIEzdF/SdMlb3ma1dfIgWiPO9i+ZVZV+tndSq\nwnFet4dePJTWIwdZ9YXeX28iWtKfXWUaRKvE4lU9xipQEjkX7Vz77G47Uml6SVYme7zmargxmU7+\nz+MNtsNIUXgn8C9gotZVWXbxpfzxb1XaNoXAMaQPbd83r3zLqmw48hnaum3cj+YKzLvaW3N91GY7\nSw0azhnngSaE2I6Fsk0I8d2I/z8DPJPsdkgkEomkZ9OTDLAlnYN7q1vzHDLAf76fSndl0AfL3EsD\nwn03elJgJpkUTimk4oBJdUYbfkxdhZHHTiQ97RzZ9R2zGl+KouBoc1jZ4HTYv8gIfYrUIoI3KP0H\ngTA3wO9IW6z81V66+Ce0NPwcIey3hVMOQrcGzwJPEGkurSlWBAsWLAveWAX7PBU812p/gv3/ClBg\n3P7wtcXOedPap3/T75/IT39dTOWfX4l5fTKbE6Eb7uW0tPQhNfUk52UNZePezw2rEG5UVa4sij3P\n7fv6hR+Pfd+hePzLzMZnRcUmtm27KXizHd4n8Xzeal2kRtUCT+0H7ffPoKZGMG1aVVKrbcZDsN2G\nfRjQWrWr+5rLiRyYkdc5M29M8oGZh+D1x9u3oxjOIas22sWqMEA8120hBG2pbRz5PtweERD3pcK6\nz/TBHytlGoRUYn6/H1VVTT39tCBXdFBxYmEhGysqDOfiBoO5aOfaF+gXM6+38HaHb2PGzbewbtUq\nw+DXWuDaW27VtWP1zp0sW7CA5WFVKKu/aGFrYwar+JCZiDAfQYViRuA41jfUBkWhb0pvfKLZ/Bri\nP0GOa7plP5r1ufYA4Tn27VMNg5mLF68O9lVP+71gh6SncEokEolEEot4UvskZybxpCXqTXoNt3bG\nS/5jUfZ4GQUfFqDu16f2qPvbDZ0XLO7W9hlxJp2PQOECq1SlWMdjlQraWUFOsxQpTvyLFkDohLYY\npgcqWmCqeepJROp2223RBzlA05lEB2YgEOTZoXstqs8Dd4UmGXKBz4SnPFun8Ea2D8AHGRPwTT0U\n9/Upyp8q7Uvovx9l8B7ov5+RV1/CshEj2KCqugy+DarKcwUFPLA49jzXBQWNMAwKKpapl+HEk64W\nbwpf9OeF5efN1kX2aVU4adb3V/gYSjQ9OhkY9yHAFxH/D29j6DpnJ1XbKM3OaA4lgs/no7R0oWWK\naLzX7ciA+Ef3wp77tb8/Gw5zsvSp2gCfm2zdhxaG/+joUW4YMoQpeXksLC0FoLx8EbW1Wzh06E1q\na7dQXr4oSk0MUPzoo/yHow9u9HPRjcrdjj7MeeQR0/6xGluKotDkcFhOzyaH/gHHD555hucLClir\nKLq2rFUUygsKeOzpp3XbcDqdLCov16Wk+p3f5Ei6yu35guH9YKwThveD2/MFR9JF1Py/5YZ/1ZSM\nRtTA926507Ifw9sS2ecrV/6Iqqo3DFO4N2/+GfPnP2s5trrbriIWMoAmkUgkki7H6gat+gKt4qDk\nzMbOTV64SsbavyS6attXjYBKqmRwSY/0ETOip//INSPRwF93BDnd7h3t5twRNJdpAYR9JL0t8d60\nm7UlOsgRW1MSeZNn2Oegmb7YXFvMgzAYBmFImw9F1aHCAlrT4ro+mT0kevnLl6nPEPx5zpwoP6pI\nY3Er4g8K2n8IYde/DCzGJ8bBHO3zE8iilGHkMZZchpFHFqX4/ROjPm+0Lqa80EczOLdRJTAWdgJF\n8RDLA+7iizNQ1Y2G31WU18nKSgm2xeWazOeNJhU7IUxp6Ne9GM/xGxFQCVZUjKeubgv19Wuoq9tC\nRcV4xo+/Sdc38V63DQPiAIfhyL/D7ePQBX8+OgfWRRx/oLDAFcDetjbW1Nezpa6O8RUV3DQ+FOCO\nrBQa6SN37Q2zqWtexe2UMBxXyDOQEj5ueYWlS19KsAeNfcoCGClNnU4nb1RV8fa8ebp14e1582IW\n/1AUBUVRaDz9LsyqwXOLPjjpuQUoqqHx9Lu6Pnnmh89QsL8ApUbRrYtKjULBRwU8/Z9PB7dvl/DP\nhgfWDh58g9raLSxe/ADTpt1lOLbGjZvF3LmPJW0udiadWoWzM5EeaBKJRHLmciZUHJR0nNKHS6k4\napKWGOGBFq9/yVednpracKalXie7H30+n5YKurUyoap1dgn8Ps/NnU19vVk1Mx/p2RczYKhIWlvi\n8wwL71d9W7yfN+H7dBKc+gX6IIe1q1GkvxYY93lW7yz2nr/X1tpito1Mx0D27noEIW7Ub6B/HpTW\ndej6ZNf/MV5vsPDjMfTGqmkPWkYEl+LxdIs6ZIsUPuvxqa+2J4QgJ2cmHPmYl6nmOkL+TetQmUMB\nDBpKff1ay/S4YcOmxuXRZkayKj/bWRMDfWh2nVOU10lNfYzW1nK9Oq//ICj9NPpQmyHr95D9dgr9\n/edyDAcNFOJhMS7XjbaO34x4Kk4mUm01atz6gVeB28N2FMhsbYZBP4ZVn4cqyz6BFjy7zqDtG1SV\nqpISFpXr576pj1zlqLC5Ep5Om5jvavh5Nqt8+lxEFU6r7cR6LZxMVz98d3lM1y3nz/rhrTume7kz\nr2c+n4/5P/oR7u3baU1Lw9HcTCa92bvz7ug1N8obM7G5GKCzPdBkAE0ikUgkXUp3mnFLuhYr8/aC\n/QVRyqp4THolXY/p+TygUvBh9PnsznZ2RZCvM4Jzke1u+OQ0vs/fRzMKj2pBMFiQVGNw28bt5m1p\nbGzsFHNpXSAijrXFdBtRbfTDoIFQ3GDaBjvXp3gfEiUSzIm8+e11uhe+z/wcO/Jc+w1qKJiRn/8M\nkyZdzqZNu2MG5+Ih3oIDQzJzWek7zPVEBxbdqNztHMxB76Go98KxG+CJNSfiCRSZYXdNNPbGC13n\nsrJU9u69F79f7w1IWincWAEjwvqrPaj08udaECk8CFlMLkVzb2blyh9ZttuI2AUQwCiwFO912yho\n0/BlA747TXwUT0Huj52MyMimb2srHx09yt62NtsG/VbBbPapmpqxOdocMDz4a4VZ4PvRR4t5aelS\ndoT5lE0sKuKBxfaDU3avZUIIci7L4UjhEdNtDXIPon53vWVwuqPXEN3aOnMm1ddfj/+yy0BRQAh4\n6y1YthEa1qJ/sLIQLSx6bdQ2Eyk6IANoJsgAmkQikZy5nCkVByUdJ9EnnD1VgfV1Jp6qqt3FmRLk\ni8Ss3cp+BVE5BHx7iUxX66xqZlbKUbMbTqO2xFOdMhGlaTLUE0ZtbBC7LZUcsa5PiTwk6mgwJ/zG\n1bzPH+yQ0sqIeNt9SWY/9vg8psGPsc5+7PEeM3g3hJXqKT//GSbNyGfT9k0x1WDJqPxstSYq1Qqj\nD43Gc9LTgbb4IONyKAylFGeth1d3GYWgwQ3snDuXJStXWrY7uHWjCr9f+Glq+oPpd6wCS4mqG+2q\n1f1+PzcMGcKaevO5NSsnhzcPheZWRx8IWLU7OvDd3uaIuZXI75l4r2Xd9bvaKMiX6RzMe9fPwj9u\nXPQX/roLlnigqSzsxVjK5GkcOLDZdh/KAJoJMoAmkUgkZy7xpPZJvjrIoNiZzZmQet0ZQb6uGLfW\nKgngjSI49SZdkdpspe5ybOxDS8MrUQqnWG2JpcDpqNI0meqJZFyf4r2ZTUYwx/R4kqC0Mtu+mdLQ\naEwIISjKycF9xFwlUzhoEJX15iqZAKaBwj1r2Je/LyrgkP9BPpMmTtIF1j4/qNDU8HeifdQ07CiQ\nTM9zM/AbNFHNcCyDH9apsD5gFqRlQN+90LuVYZ8eZb/fvgLLDDPVI1wJ/IWOpsjGQzyK0il5eWyp\nqzM9/qkuF1vbjz/RlHSzBwLPzp/PDreb9NZWmhwOWjMH8Kd374G0Kujr1jzpTjngRCFKyyTmzdub\n8AOOeK9l3fG72jQ99teD4cVfasqzSISA2x6Hw38JvADMBkzGf9p8Upw/5lzXWbbV5J0dQJNFBCQS\niUTS5ZyJFQclHUcGz85c4qmq2p1YGeD7z/dTubXS8L1IjEynSx8u7TRDY2vjfnCe86eYhu7Jwqqg\nxYG/1zBv3t6422JmLh2rwptdkrG2xCo6EM/1KZ6KrUIIWlvjK65gh8DxxGv0b0XkvBg9aTRXTh3G\nnDna+Bw8uMh0TCiKwsm0NMvqhCfT0mwXOogcQw5nkxY8iyxOdJ6fD458wKrPV+kKOjRNr4WM8WhB\nqujWxCq6YLkm/hUYj61CFNbVLJ8FHoLmSk0ldeQg/f3nWtYV6Ntqbx02rfDLFGCD4Xc6q6BPPEV0\n4jHot1ex9rTuBaNqswFPs/EVFWypqwsWLnjo3d0MUr4HRSs038Tieu3vGysQ6Qt5883tCfdJvNey\n7vhdbVgQDCAzwzh4BtrrGamEGqkARuPfp83Pmypou/tkXNWQO5te3bZniUQikXxtCfxYWrB4AZXu\niPSbF5Jrxi2RSDqO7kbE5NF/eOXD7iCeIJ9VO3VP1YtCT9UrDlSwbdq2pKeB2ml35oB0DuzajBAC\n1eTm0Wi7iZ4Pp9NJ+dJyyimP2k55+SLKy5Oj+uqJQfVkXJ/KHi9j27RtVAtjRc3iF0I3s/oAivHk\nsltBM+qbcQTn7Ki+jObFS/teov9b/cnol4HSqw3aHIi0AsNtTCwsZFNFBTP80YEBo+qEdggGCre6\ntXZF8ldgEpoSLPgltOBWYTW8vsAgJTl2oMhyTTwIXG38Pf/5firdlZQT2mdh4UQqKjYZqAR3AIvC\nW8YxHFbLME0Oe+uwFlhdZPDOg2h1Lv1oiaJ6VeHixatjbtsu4ePOas0J//yDZWXctG0bwsygf7E+\nUFQ4pZCKAybKrI9UvpE/FM+n0yLUsPrg77Pz53N/+/4CKGiFDVaJZm4/CJ5RYW+M8APVNGw+kdA6\nKYSgWW22vCY0K81R/Wdn3UqmotpwzinAiUZNaWamQGs8HvhP+985wHp0icnBashh2w8EoYUWhO6u\nTBWpQJNIJBJJtxD4sVT7Ti2Hdh2i9p1aypeWy+CZRNJDiUdV0x3YURvYCfIZPlU3UY90SbtPgfdT\nL8PGDmPI5UMs1XCdoZwz66+eGPxKFh29PsWjqAEtgKKqmwy31RHVj7W6CeIJzhnOixYQuwRfTvyS\ng7MOxlSJPFhWxvKCAjaoarhIhg3twY8HFiemkrEMQh8ELjD5Yr4f0n9DuGTHSIFkhuGaKIBU4lLr\nlpU9SEHBclR1Q1hb/EBK1IYaKGSdyS38BptBSOvAqhNYTXr6E52ievX5fJSWLiQvbwq5ubPJy5tC\naelC3VgJH4+Rnx89+gaGXTmTP8+ZwzSXi1k5OUxzuagqKTGsbhlLmfXnLVtjqmF3uN1MNwj6ghZE\nO3ufwRv5fprVIwmtk4qi0PjFCctrWeMXJ6K2bbZuAcHrwnmXnZeU64LlnBvkgaq3DL+n7tpFdh8v\nKQP6op7Xl5QBfbno0vfJz39GP/77umF4x9XknYH0QJNIJBKJRCKRxKQjlQ+7ii7xr+oErzfTdjcD\nv0BT0FyApZfSmVpA4euALdWjTS+xeEmWB5rhvPgDcB56dVdg2ybzzefzsWzBAsvqhImoZAzbJ4DX\ngJvNv5f+qpOzW8Zx+nR63H58ph5QPwH+jbgM3Q0LWjQcw+fbHbGhwwxShrFKNDOT0C7XAqV90tix\n/wCDBw+O2Xa7FVSTqViKt9qsnc+np6fHVOV2pOCIEILZubmWhQvGOmHP/UR1ZfqrTnz7PAn1X+bA\nXHxTDusrsAbYp+LcmoP3s4Mxt+Pz+Rg3eRxHvR9w1lHo74djKnx5LpybOZJdv9+V8Npi6QH4ejbc\ncT+MHx+swqm89RaOF1bQOvEIYqTQXaNG7BvBpDGz2LjxbVpa+vCpupm27zeb7tuqGrL0QJNIJBKJ\nRCKRdDvxqmq6g476wHSX15tZu1kPXEXIiLy9DUZquK5WzknsE+sG2ul0snPnakpKqpKu+jFWN8Wn\ntDKdFxbqLjOViNPpZFF5OVtqa3nz0CG21NayqFyvkklEPWmoBlOAFiyVPAMysqmr25qQH5/Zmnhx\n7sVxq3WNfN3uuuv6aGVi2lMc+acWbr8chvfTgjfD+8Htl8PHRS0sLV9qq+12VY/JVJqa+a75/TOo\nrr6PBQuW2fz8RN5/fxA5OdcwZMgNhiq2cDqqKG1yOCxt1I5HCwVBQHZ6/4RTrzN6jQZ3gVb5OPya\nsE8FdwEZvb5h6zr00OMP4a35gF/ug/0eeNun/f2LGvDWfMDDjz8cd/sCWKnS8TXA60tg3m3wYDHM\nuw3xUhkt4w8jCkTUNWpf/j5SM08Ex3/ugEEdVpN3FlKBJpFIJBKJRCKJm55aVbUjagOIv4JiZ7a7\n4csGfHf6bKnhzoQqqRJ7JHtuJaPyadT4sqHuslKJRLavo+pJUzXYm8AoNM+zCJJdnTBw3pKl1jVU\nJvbP04zqw89D2L/tzvPOVD2aEW+1WePP+9A82u4DwtttrGJLBJ/Px/z5z+J276C1NR3Vu4eVjfVc\nbxA3caMFLz3X6l/v6NjSjv11SHsc+laGVfgsguYncblutFUNdciATFZ+4Qt3Fwu1XYG7z3Zy8DNv\nQm20PecCY/QV4A6MT/8pcL7qJPvsbFpTWvF+6qXxqkbE8Og+D+9bo7VSKtAkEolEIpFIJD2Onhg8\ng46rDbrL6y2y3QfePkDm2Zm21HBnSpVUiT2SPbeSUfk0al7YUHfZVYkkQz1ppgabe/VcCvZ3TXXC\nSEP3jqp1I5WJgwcXkZJ+RD/PI/5td553purRiHirzZp//lngfuBawgdLpIot0bUuEFisqBhPXd0W\n6uvXcMj3PnPEENxECIRVldI+aXhdStLHlqYQ/KtW4OJYLRw5pP3dXI6q7rDliyiEoI+3ietM3p8p\noI+nKeG+MhvnTo8zumiHlTdgM/C/4PuWL1gp13erD7FdwD6i+nZEzQiaPX0sffQ6E6lAk0gkEolE\nIpFI2ulJXm/xqOG6Szkn+WoQV3XawLzYBuQSlwea0T47Qz0ZfjwdVaV2lHgVhVZVKIeNHdYp87wz\nFcXB82zTdy2A8eenAGbb8OIccBHZ56XQmtKKo81B4ZRCyh4vs32ezT0DffTjNvKcfyI3Mz3o3Tfn\nkUdYWr406WMrGQpBIQTjHCnsbjOP91yWorCrtc303MczLgJxpdxxudTPNPCMM1OgmXkpNgPrwel1\nkpmdicPvYMakGfxxwz5qah429cX78MMPpQJNIpFIJBKJRCLpCnqS11s8arieXiVV0vOIp2qr0bwY\n4hnCWTvOikvdFblP1yUuPm/6PGH1pNnr4Tf93V31204Aws65UBSlw/PcTn8lA6PjyRzoRVHeMPy8\nUbXZaJ82AZip2HyQMQHf1ENBFZNVRVgz3O4d7YGZSJwc502OZV+q8+4bPHhwp4ytZCgEFUXhuFCt\nRKIcF2rUuU+0mrOiKNZVpYcA+w1eN/NSTANmw8nGVsThMfDl+fz19weoqXnIto9eZyAVaBKJRCKR\nSCQSiQnd6fUWjxquJynnJB2jK8ZcR33Hwv2+7Kq7klW10ufzMf/J+bi3uhNWGvUk4jkXiczzru4v\nq+NxbOhDS8MrCHEjsVRVxiosEwVaWincVAH5iVdgFkKQmzub+vo1pp/JyZnFoUNvdvk1IZE1QQjB\neRl5rDrxMTMN3ncDc/sO5ZPGWp1as6N+hLGqSitXKZq3mQL4gVeB2y02uCpHS2EF4ErgL1j56K1e\nvVQq0CQSiUQikUgkku6gO73e4lHD9STlnCR+ElV9JEpHfcfC/b7sKnDM9skwjJUpRKuqAjf4FUcq\nOqQ06knEcy7inefd0V9Wx9M64ySjxz1tS1VlpMJyOj9DUdZH77SvG4ZHB89AXxHWSjykKAoORxNW\nxn4OR1O3XBMS2aeiKPQ628UcCnCj6Pzb3CgUU0Cvs126bSfDj9C0GvYhlZGDRlJ8TnFo7K514Wxz\nWnopcspBqDFnYxw80xoa7qPXWUgFmkQikUgkEolEcgYQrx9NTy30INGTDNVHvHRH1VbTfTYDvwEu\nR6vcZ6GqKn24lIojFdoNfgTJrqrZVXTkXMSa593RX3aPJxFvuMbGRgNVmh8GDYTiBtPvpr/q5OyW\nyzh9OgOHo4nCwomUlT0YNa/MPdBAVTdQUlJFefkiB8ATxwAAIABJREFU223ubkpLF7JixcVkiu2c\nTSVZtOLBwRcU4VWuYt68vbrjSda6YEeZGjj/poo1gH0qvF6iFVMArD3wNB+91auflgo0iUQikUgk\nEonk6048N5syeHbmkAzVRzx0R9VWy32mAd+B9B3pMVVV7q1u4xtt9EqjM4WOnotY87yr+yue44l3\njVIUxcQbbDrO1NOWKqamL/ry8cdbqa9fQ13dFioqxjN+/E1RCryysgcpKFiOqm4gXD6lqhsoKHiO\nxYsfiKvN3U1Z2YNceOGL+NQZfMQB9nCIjziAT53BhReu0h1PMtcFO8rUwPk3U6yxTwV3ATSHeylO\nBMJ98UIY+eh1BjKAJpFIJBKJRCKRSCTdRFcHOSyNvgEEONocSQ3CxtxnKgzIHmB5w90dgb/OpjPP\nRXf0V1eMLafTSXn5Imprt3Do0JvU1m7hrn+5w7S4AjUqnPgOdkznk2He35OIPp7ZpsfTWecu1ueN\n0pJ7vdBbU5417gTC+/xBYDmwlu4KcMoAmkQikUgkEolEIpF0A90VFOqOqq1292l2w90dgb+uoLPO\nRXf1V1eOrdgqJgxUTBp+/wwqK3dEvW4UoCsvX9RlwbNkz/V4jqe7qjlHKtb+/V8fRm29Fn3wDMCJ\nohRz8cUrui3AKQNoEolEIpFIJBKJRNINdFeQw9Toe7/mO7Z4QXTAoSfss7tu8DuTzjwX3dFf3TG2\nzIorpG/OM1AxBYhtOt9VwVifz0dp6ULy8qaQmzubvLwplJYuTHqRh1jH0x3nzqiNVqm0F164ij//\n+bfdFuCURQQkEolEIpFIJBKJpJuwMtHuTGN8O0bfPW2fpgUXDAoOnEl01rnorv7qjrEVTsBjLS9v\nCnV11qbztbVbO709Vvh8vvbCCPfj908ncJJUdRMFBcu7PHW0u8+drh0LllFZuYPW1r44HCcoKprI\n4sUPWLZjz549nVpEQAbQJBKJRCKRSCQSiaSb6AlBoe6o2proPnvKDX5nkexz0d391Z0Vgc+Eqpo9\nuY09pZqzWTuMXpcBNBNkAE0ikUgkEolEIpF8FejuIMeZSk+5wT9T+Lr1V0jddV97gCqg7tpIQcFz\nPaIwQGyV3DRqa7d0dbN6LD6fj/lPzse91U1rSiuONgeFUwope7wMp9PZ6QG0XsneoEQikUgkEolE\nIpFI7BMw0S6n/GsX5OgIsp/i4+vWX4EqlFoq4PKIVMDuD54JIWhtTceqikjAp+3rdu6M0Kl1i0Jq\n3YoDFWybto2dm3d2ehtkAE0ikUgkEolEIpFIegjyRlkiSR6BKpTl5T1PgacoCg5HE5pRvrECzeFo\n6lFt7k7mPzlfC55dEOYXqYD/fD/VopoFixdw53fu7NQ2yCqcEolEIpFIJBKJRCKRSL7S9MRAVGHh\nRFR1k+F7qrqRoqIru7hFPRf3VrdhsRXQgmiVWys7vQ0ygCaRSCQSiUQikUgkEolE0sWUlT1IQcFy\nVHUDmhINNJ+2DRQUPMfixQ90Z/N6DEIIWlNarbJdaVVb6WyPfxlAk0gkEolEIpFIJBKJRCLpYgI+\nbSUlVbhc08jJmYXLNY2SkqoeUeSgp6AoCo42RyjGGIkAR5uj01WG0gNNIpFIJBKJRCKRSCQSiaQb\n6Mk+bT2JwimFVByoMEzjVD9SKZpa1OltkAo0iUQikUgkEolEIpFIJJJuRgbPzCl7vIyCDwtQ96vh\n2a6o+1UK9heweMHiTm+DDKBJJBKJRCKRSCQSiUQikUh6LE6nk52bd1IyuASX20XO2hxcbhclg0vY\nuXlnl6S7yhROiUQikUgkEolEIpFIJBKJJd2dYup0OilfWk455d3SFqlAk0gkEolEIpFIJBKJRCKR\nROHz+SgtXUhe3hRyc2eTlzeF0tKF+Hy+bm1XdwTypAJNIpFIJBKJRCKRSCQSiUSiw+fzMX78TVRX\n34/fvwhQAEFFxSa2bbvpa1cpVCrQJBKJRCKRSCQSiUQikUgkOubPf7Y9eDYDLXgGoOD3z6C6+j4W\nLFjWnc3rcmQATSKRSCQSiUQikUgkEolEosPt3oHfP93wPb9/BpWVO7q4Rd2LDKBJJBKJRCKRSCQS\niUQikUiCCCFobU0npDyLRKG1tS9CiK5sVrciA2gSiUQikUgkEolEIpFIJJIgiqLgcDQBZgEygcPR\n1K1VObsaGUCTSCQSiUQikUgkEolEIpHoKCyciKpuMnxPVTdSVHRlF7eoe5EBNIlEIpFIJBKJRCKR\nSCQSiY6ysgcpKFiOqm4gpEQTqOoGCgqeY/HiB7qzeV2ODKBJJBKJRCKRSCQSiUQikUh0OJ1Odu5c\nTUlJFS7XNHJyZuFyTaOk5P+zd+fxUVX3/8dfn4GQEBgIAYWwJYEAAipKXEBEWawgBbQVrSgKaFW0\ngOJeQaEWtAiIiKBoq+DaVql1q7tofyqghK9VISqgAQVUkC2AgUDO7487WSaZDCHJZJLwfj4e8yBz\n5txzz53MXGbeOefc5Sxduhi/3x/tLlaputHugIiIiIiIiIiIVD9+v585c6YwZ453YYEjac2z4jQC\nTUREREREREREwjqSwzNQgCYiIiIiIiIiIhKWAjQREREREREREZEwFKCJiIiIiIiIiIiEoQBNRERE\nREREREQkDAVoIiIiIiIiIiIiYShAExERERERERERCUMBmoiIiIiIiIiISBgK0ERERERERERERMJQ\ngCYiIiIiIiIiIhKGAjQREREREREREZEwFKCJiIiIiIiIiIiEoQBNREREREREREQkDAVoIiIV8Oyz\nz0a7CyIiOheJSNTpPCQitV2lB2hm1tvMXjKzjWaWZ2ZDy7BNHzPLMLMcM/vazEZWdr9ERCJBHxZF\npDrQuUhEok3nIRGp7SIxAq0B8ClwLeAOVdnMUoBXgHeAbsAc4K9m9qsI9E1EREREREREROSw1K3s\nBp1zrwOvA5iZlWGTa4BvnHO3BO5/ZWanAxOAtyq7fyIiIiIiIiIiIoejOqyB1gN4u1jZG0DPKPRF\nREREREREREQkSKWPQCuHFsCPxcp+BBqZWaxzbl8p28UBZGZmRrJvIiJh7dy5k5UrV0a7GyJyhNO5\nSESiTechEYm2IvlQXCTarw4BWnmlAIwYMSLK3RCRI116enq0uyAionORiESdzkMiUk2kAB9VdqPV\nIUD7AWherKw5sCvM6DPwpnleAmQBOZHpmoiIiIiIiIiI1ABxeOHZG5FovDoEaEuBc4qVnR0oL5Vz\n7mfgmUh1SkREREREREREapRKH3mWr9IvImBmDcysm5mdEChqF7jfJvD4PWa2qMgmDwfqTDezTmZ2\nLTAMuK+y+yYiIiIiIiIiInK4zDlXuQ2anQksAYo3vMg5d7mZPQ4kO+f6FdnmDGA20AX4HrjLOfdk\npXZMRERERERERESkHCo9QBMREREREREREalNKn0Kp4iIiIiIiIiISG1SIwM0M/uDmX1rZr+Y2TIz\nOznafRKR2snMJptZXrHb6mJ17jKzTWa218zeMrO0aPVXRGoHM+ttZi+Z2cbAeWdoiDphzz1mFmtm\n88xsq5llm9nzZnZ01R2FiNR0hzoXmdnjIT4n/adYHZ2LRKTczOyPZvaxme0ysx/N7AUz6xiiXsQ/\nF9W4AM3MfgfMAiYDJwL/A94ws2ZR7ZiI1GZfAM2BFoHb6fkPmNmtwFjgKuAUYA/eOaleFPopIrVH\nA+BT4FpKritb1nPP/cCvgfOBM4CWwOLIdltEapmw56KA1wj+nDS82OM6F4lIRfQG5gKnAmcBMcCb\nZlY/v0JVfS6qcWugmdkyYLlz7rrAfQO+Ax5wzt0b1c6JSK1jZpOBc51z3Ut5fBMwwzk3O3C/EfAj\nMNI598+q66mI1FZmlgec55x7qUhZ2HNP4P4W4CLn3AuBOp2ATKCHc+7jqj4OEanZSjkXPQ40ds79\ntpRtdC4SkUoVGDz1E3CGc+6DQFmVfC6qUSPQzCwGSAfeyS9zXgL4NtAzWv0SkVqvQ2Dqwjoze8rM\n2gCYWSreX1qLnpN2AcvROUlEIqSM556TgLrF6nwFbEDnJxGpXH0C06q+NLP5ZpZY5LF0dC4SkcqV\ngDcidhtU7eeiGhWgAc2AOnhJYlE/4j1hIiKVbRkwChgAjAFSgf+aWQO8845D5yQRqVplOfc0B/YH\nPkCWVkdEpKJeAy4D+gG3AGcC/wnMEgLvfKNzkYhUisC55X7gA+dc/rrUVfa5qO5h91hE5AjinHuj\nyN0vzOxjYD1wIfBldHolIiIiEn3FlqtYZWafA+uAPsCSqHRKRGqz+UAXoFc0dl7TRqBtBQ7ipYdF\nNQd+qPruiMiRxjm3E/gaSMM77xg6J4lI1SrLuecHoF5gzY/S6oiIVCrn3Ld439nyr36nc5GIVAoz\nexAYBPRxzm0u8lCVfS6qUQGacy4XyAD655cFhvD1Bz6KVr9E5MhhZg3xPhRuCnxI/IHgc1IjvCvE\n6JwkIhFRxnNPBnCgWJ1OQFtgaZV1VkSOKGbWGmgK5H+51blIRCosEJ6dC/R1zm0o+lhVfi6qiVM4\n7wMWmlkG8DEwAYgHFkazUyJSO5nZDOBlvGmbrYA/AbnA3wNV7gcmmdlaIAv4M/A98GKVd1ZEao3A\nOotpeH9RBWhnZt2Abc657zjEucc5t8vM/gbcZ2bbgWzgAeBDXfVORMoq3LkocJsMLMb78poGTMcb\nqf8G6FwkIhVnZvOB4cBQYI+Z5Y802+mcywn8XCWfi2pcgBa4BGkz4C684XafAgOcc1ui2zMRqaVa\nA8/g/TV1C/AB3qWOfwZwzt1rZvHAArwrwvw/4Bzn3P4o9VdEaoeT8NYPcoHbrED5IuDyMp57JuAt\nffE8EAu8DvyharovIrVEuHPRtcDxeBcRSAA24QVndwZmDuXTuUhEKmIM3vnnvWLlo4EnoMzfySp8\nLjLnXDn6LyIiIiIiIiIicmSoUWugiYiIiIiIiIiIVDUFaCIiIiIiIiIiImEoQBMREREREREREQlD\nAZqIiIiIiIiIiEgYCtBERERERERERETCUIAmIiIiIiIiIiIShgI0ERERERERERGRMBSgiYiIiIiI\niIiIhKEATUREREREREREJAwFaCIiIiJHADP71szGR7sfIiIiIjWRAjQRERGRSmZmj5vZvwI/LzGz\n+6pw3yPNbHuIh04CHqmqfoiIiIjUJnWj3QEREREROTQzi3HO5ZalKuCKFzrnfq78XomIiIgcGTQC\nTURERCRCzOxx4EzgOjPLM7ODZtY28NixZvYfM8s2sx/M7Akza1pk2yVmNtfMZpvZFuD1QPkEM/vM\nzHab2QYzm2dm8YHHzgQeAxoX2d+dgceCpnCaWRszezGw/51m9g8zO7rI45PN7P/MbERg2x1m9qyZ\nNaiCp05ERESkWlGAJiIiIhI544GlwKNAcyAJ+M7MGgPvABlAd2AAcDTwz2LbXwbsA04DxgTKDgLj\ngC6Bx/sC9wYe+wi4HthVZH8zi3fKzAx4CUgAegNnAe2Avxer2h44FxgE/BovDLztsJ4BERERkVpA\nUzhFREREIsQ5l21m+4G9zrkt+eVmNhZY6Zy7o0jZ74ENZpbmnFsbKF7jnLutWJsPFLm7wczuAB4C\nxjrncs1sp1etcH8hnAV0BVKcc5sC+78MWGVm6c65jPxuASOdc3sDdZ4E+gN3hGhTREREpNZSgCYi\nIiJS9boB/cwsu1i5wxv1lR+gZRR7HDM7C28U2DFAI7zPc7FmFuecyynj/o8BvssPzwCcc5lmtgPo\nXGS/WfnhWcBmvJFyIiIiIkcUBWgiIiIiVa8h3hTKW/BGeRW1ucjPe4o+YGbJwMvAPOB2YBveFMy/\nAvWAsgZoZVX8ogUOLQEiIiIiRyAFaCIiIiKRtR+oU6xsJfBbYL1zLu8w2koHzDl3U36BmV1Uhv0V\nlwm0MbNWzrmNgXa64K2Jtuow+iMiIiJyRNBfEEVEREQiKws41cySi1xlcx6QCPzdzE4ys3ZmNsDM\nHgss8F+atUCMmY03s1QzuxS4OsT+GppZPzNramb1izfinHsb+AJ42sxONLNTgEXAEufc/1XoaEVE\nRERqIQVoIiIiIpE1E+/KmauBn8ysrXNuM9AL77PYG8BnwH3AduecC2znijfknPsMuAFv6ufnwHCK\nXRXTObcUeBj4B/ATcHMp7Q0FtgPvA2/ihXPFR7OJiIiICN4UgGj3QUREREREREREpNrSCDQRERER\nEREREZEwFKCJiIiIiIiIiIiEoQBNREREREREREQkDAVoIiIiIiIiIiIiYShAExERERERERERCUMB\nmoiIiIiIiIiISBgK0ERERERERERERMJQgCYiIiIiIiIiIhKGAjQREREREREREZEwFKCJiIiIBJhZ\nJzPLM7MLy7FtbGDbWyLRNxERERGJHgVoIiIiUm0FAqlD3Q6a2RmVuFtXwW0rsr2IiIiIVEN1o90B\nERERkTBGFLs/EjgrUG5FyjMrY2fOua/MrL5zbn85tt1nZvWB3Mroi4iIiIhUH+ac/kgqIiIiNYOZ\nzQWudc7VKWP9OOdcToS7JYfJzOKdc3uj3Q8RERGRstIUThEREakVzGxAYErnb8xsupltBHabWT0z\na2Zms83sCzPbbWY7zOxlM+tSrI0Sa6CZ2d/NbIuZtTGzV8ws28x+NLNpxbYtsQaamf0lUNbGzJ4K\n7HebmS0ws3rFto83s/lm9rOZ7TKz580suSzrqplZnJlNNbMMM9sZ6OMSM+sVoq7PzG4ys8/N7JfA\nsbxqZscXqzfazFaY2Z5An941szNLO9Yi2/1gZvOL3B8TqNvTzB4xsy3AmsBj7QLPxddmtjfwPD9r\nZq1DtJtoZg+Y2Xozywn8+5iZNTKzxoFjuSfEdqmB/V8X7jkUERERCUdTOEVERKS2+TOwB5gONAAO\nAp2AgcDzwHogCRgDvGdmXZxzW8O054AY4C3gPeCmQFu3mdnXzrlFh9jWAf8GvgZuBU4Bfg9sAv5U\npO6zwGDgMSADb6rqvynbmmpNgcuAvwMPAwmBfbxlZt2dc18Wqfs08DvgRWABUA84EzgZ+AwgEETd\nGjjeSXjPYQ+gD/D+IfpSvL/59x/FO+Y7gbhAWU/gROApYCPQHrgW6G5mxzrncgP9aQR8BKQAfwX+\nBxwNnAe0cM59bWavAMOBPxbb/wjgAN7zKyIiIlIuCtBERESktjGgl3PuQEGB2SfOuc5BlcyeBVbh\nras26xBt+oG7nHP3Be4vMLMvgCuAcAFafn8+dM6NL7Jti8C2fwr0pScwBLjbOTcpUO9hM3sGOL54\ngyFsBlKdcweLHN9f8UZ6/QEYFyg7By88+4tz7vYi299XZLvOwC3AM865omvQPVCGfoSzyTl3drGy\n551zTxctMLPX8YK7ocDiQPFEoANwjnPuzSLVi44CfAL4rZmd4Zz7b5Hyi4G3nXM/VbD/IiIicgTT\nFE4RERGpbR4rGp4BFL0ogJnVMbNEYAfwLdC9jO0+Uuz+B0C7Mmzn8EZ6FfX/gJZmFhO4PzBQ76Fi\n9eYSfLGE0DtwLi8/PDNPE6AOsJLg4zsf2E9w8FTc+YF//xSmzuEK9RzgnNuX/7OZxQR+L6uBvQT3\n+7fA8mLhWXGvAVuBS4q0eRLe6MMnK9R7EREROeIpQBMREZHaJqt4QWDdr1vMbB2wDy9o+QlvVFPj\nMrS5wzm3u1jZdqBJGfu0IcS2hjfVEiAZ2Oec21is3toyto+Z/T4wKm4f8DPe8Z1F8PG1AzY45/aE\naaodsN85t6as+y6jrOIFgXXfppnZ90AOhb+X+gT3OxX4IlzjgdD078CwIsHkJcBuvKmwIiIiIuWm\nAE1ERERqm19ClN0F/AV4A2+drLPxwqW1lO3z0MFSyg85OqyStg/LzH6PN0LuC7wpqQPwju//EZnP\ne+HWZSvtCqmhfi+P4K0p9yQwDPgVXr+zKV+/n8ALNX9tZj686ar/cs6F2reIiIhImWkNNBERETkS\nnA/8xzl3bdHCwJTBddHpUpD1QKyZtSo2Cq1DGbc/H1jlnLuoaKGZ3Vus3jrgNDNrGGJEXdE69cys\no3Pu61AVnHP7zewXCkfQ5e8vHmhWxj6DNzXzEedcwcL/ZtYQaFSs3rfAsYdqzDmXYWaZeCPP9gAt\n0PRNERERqQQagSYiIiK1SWkjow5SbLSXmV2Kd/XK6uANvP5dW6x8HGW7Cmeo4zuDkuu7Lca76ubE\nMG39K/Dv5EPscx1wRrGy4v0/lIOU/Dw6IUS9xcCpZjagDG0+iXc10z/gXfXz3cPsk4iIiEgJGoEm\nIiIitUlpUyJfAW42s0eAT4BueNP7sqqoX2E55z4ys1eB2wJX6FwB9Mdb+wsOHaK9Asw3s+fxwrg0\n4Cq8BfkLAirn3Otm9hxwi5l1Ad7C+zx4JvCKc+5vzrlMM5sJ3GRmrYAXgVzgVGCtcy7/4gJ/Be43\ns78DS4B0vEBt52Ec+qvA7wOj2b4GTgd64V3goai7gd8AL5nZ34BP8Ua6nQeMKDZS7ilgKt5VTe9z\nzpUlgBQREREJSwGaiIiI1DThApHSHpsCxAIX4q2B9gneOmjzQmwTqo3S2g21bVnaC+V3wMzAv8OA\nN4FL8dY1yznEtgvwAqXfA+cAq4ALgCuA44vVHQ5kAKPxnoOdwPLAzeuwc7ea2Rq8UVzT8KZD/g94\ntEg784A2eGuu/RpvpNevAu2U9ZjHBI7tMryRcf/FWwPtw6JtOOd2mdlpeGvZnRvo+w94AeAPRRt0\nzn1vZu8BffHCNBEREZEKM/1RTkRERKR6MrMewEfA+c65F6Ldn5rCzP4DtHHOHRftvoiIiEjtoDXQ\nRERERKoBM4sLUXwd3vTJD6q4OzWWmSXjjYRbFO2+iIiISO2hKZwiIiIi1cMdZnYM3jRGh7cQfn9g\njnNuS1R7VgOYWTu89dPG4E05/Vt0eyQiIiK1iQI0ERERkerhA6APcCfQAFiPd7XM6VHsU03yK+Ah\n4BvgEufc9ij3R0RERGoRrYEmIiIiIiIiIiISRo0dgWZmTYEBeJefP9SVqUREREREREREpPaKA1KA\nN5xzP1d24zU2QMMLz56OdidERERERERERKTauAR4prIbrckBWhbAU089RefOnaPcFREpbsKECcye\nPTva3RCRUug9KlJ96f0pUr3pPSpSPWVmZjJixAgI5EWVrSYHaDkAnTt3pnv37tHui4gU07hxY703\nRaoxvUdFqi+9P0WqN71HRaq9iCzz5YtEoyIiIiIiIiIiIrWFAjQREREREREREZEwFKCJiIiIiIiI\niIiEoQBNRCJi+PDh0e6CiISh96hI9aX3p0j1pveoyJHJnHPR7kO5mFl3ICMjI0MLOIqIiIiIiIiI\nHMFWrlxJeno6QLpzbmVlt1+Tr8IpIhJ1GzZsYOvWrdHuhoiIiEhUNWvWjLZt20a7GyIiEaMATUSk\nnDZs2EDnzp3Zu3dvtLsiIiIiElXx8fFkZmYqRBORWksBmohIOW3dupW9e/fy1FNP0blz52h3R0RE\nRCQqMjMzGTFiBFu3blWAJiK1lgI0EZEK6ty5s9ZiFBERERERqcV0FU4REREREREREZEwFKCJiIiI\niIiIiIiEoQBNREREREREREQkDAVoIiIiIiIiIiIiYShAExERERE5gi1cuBCfz8eGDRui3RWpht5/\n/318Ph///e9/o90VEZGoUoAmIiIitYa+6IkcPjPDzKLdDanG9PoQEVGAJiJSpZxzNbJtqd70ugqm\nL3qH55577uHFF1+MdjeqnUi/9mvie+tIod+9iEjNkp2dzfjxkxk8eExE96MATUQkwvJP6KmpZ9Gm\nzXmkpp7F+PGTyc7OrtZth7J3796ItFuZDh48SG5ubrS7EXHZ2dmMv2U8qd1TaXNKG1K7pzL+lvGV\n97qKUNtS/dx9990K0AKys7OZPH48Z6Wmcl6bNpyVmsrk8ZX32o90+1J+2dnZjL/9dlJ79aJN//6k\n9urF+Ntvr9TffSTbFxE5UmVnZ9Oz5/nMm9eTzZsfiui+FKCJiERQ0RN6VtZbbNz4IllZbzFvXk96\n9jy/Qh+cI9k2wJQpU/D5fGRmZnLxxReTmJhI7969GT16NH6/n++++47Bgwfj9/tp3bo18+fPB+Dz\nzz+nf//+NGzYkJSUFJ599tmgdg8cOMCf/vQnOnbsSP369WnWrBm9e/fmnXfeKagzatQo/H4/3377\nLQMGDKBhw4a0atWKP//5z0FtrV+/Hp/Px3333cecOXNIS0sjLi6OzMxMALZs2cIVV1xBixYtqF+/\nPieccAJPPPFEqW3cf//9pKSkEB8fT58+fVi1alWFnsNIyc7OpufZPZm3eR5ZQ7PYOHgjWUOzmPfD\nPHqe3bPir6sItS1SnWVnZ3N+z570nDePt7KyeHHjRt7KyqLnvHmc37Pir/1Itr9hwwauvfZajjnm\nGOLj42nWrBkXXngh69evL1F39erV9OvXj/j4eNq0acO0adPIy8srUe+ll15i8ODBtGrViri4ONLS\n0pg6dWqJun369OH444/n888/p0+fPjRo0IAOHTqwePFiwJtW3aNHD+Lj4znmmGOCzvXVRXZ2Nj0H\nD2ZeQgJZU6ey8c47yZo6lXkJCfQcPLhSfveRbH/37t1cf/31pKamEhcXR/PmzTn77LP59NNPC+rM\nmzeP9u3bEx8fT48ePfjggw/o06cP/fr1C2pr48aNnHfeeTRs2JDmzZtzww03sG/fPo2aE5Fqa+LE\nmWRm3kBe3kAgsrMQFKCJiERQ6BO6kZc3kMzMCUyaNKtatg2F0+AuuOACcnJyuOeee7jyyisBb5TX\nOeecQ3JyMjNmzCA1NZVx48axaNEizjnnHE4++WTuvfdeGjVqxMiRI4O+xE2ePJm77rqL/v37M2/e\nPCZNmkRycjIrV64M2ndeXh4DBw4kKSmJGTNmcNJJJzF58mSmTJlSoq+PPfYYDz74IFdffTWzZs0i\nMTGRnJwczjzzTJ5++mkuvfRSZs6cSUJCAqPyfydKAAAgAElEQVRGjWLu3Lkl2li0aBFz585l7Nix\n3H777axatYr+/fuzZcuWCj2PkTDxzxPJTMskLy2v6K+evPZ5ZKZlMmnqpGrZNlTPL3qLFi3C5/Px\n4YcfMn78eI4++miaNGnCmDFjOHDgADt37uSyyy4jMTGRxMREbr311hJt7N27lxtvvJG2bdsSFxfH\nMcccw6xZJd+DPp+P8ePH8/zzz9O1a1fi4+M57bTT+OKLLwBYsGABHTp0oH79+vTt2zfkou7Lly9n\n4MCBJCQk0KBBA/r06cNHH30UVCc/AF+3bh2jRo2iSZMmJCQkcPnll5OTkxPUn7179xYsIu/z+bj8\n8ssBL8hOTU0tsf/8tiv7uKJt5sSJ3JCZycC8vKIvfQbm5TEhM5NZkyr22o9k+5988gnLli1j+PDh\nzJ07l2uuuYZ33nmHvn37Bv2+f/zxR/r06cNnn33G7bffzoQJE3jyySeZM2dOiTYXLlyI3+/nxhtv\n5IEHHuCkk07izjvv5I9//GNQPTNj27ZtDBkyhB49ejBjxgzi4uIYPnw4//znPxk+fDiDBw9m+vTp\n7NmzhwsuuIA9e/aU+1gjYeI995D561+Td8opkD8F3Iy8U04h89e/ZtJf/lKt27/66qtZsGABF1xw\nAQ899BA333wz8fHxBX9Meuihhxg3bhxt27ZlxowZ9O7dm/POO4+NGzcGtZOTk0O/fv146623GD9+\nPJMmTeKDDz7glltu0dR4Eak2srNh5Ur45z9h2jR47LEPycsbUDU7d87VyBvQHXAZGRlORCQaMjIy\n3KHOQykp/R3kOXAhbnmuZcuzXEaGK9ctKSl82ykpZ1Xo+KZMmeLMzI0YMSKofNSoUc7n87np06cX\nlO3YscPFx8e7OnXquOeee66g/KuvvnJm5v70pz8VlJ1wwgluyJAhYfedv4/rr78+qHzw4MEuLi7O\n/fzzz84557KyspyZuYSEhIKyfPfff7/z+Xzu2WefLSg7cOCAO+2001yjRo3c7t27g9po0KCB27x5\nc0Hdjz/+2JmZu/HGG8P2NRpSTkxxTMYxJcRtMq5lt5YuY1NGuW5JxyeFbTule0qF+n7xxRe7uLg4\nd/PNN7vHHnvMzZgxw5177rnumWeecc45N3/+fGdmrk+fPu7BBx90N910k2vatKlLS0tzffv2LWjn\nl19+cR07dnTx8fHuj3/8o3vggQfcySef7Lp16+Z8Pp97//33y9ynhQsXOjNzJ554ohs0aJB76KGH\n3MiRI53P53O33nqr6927txsxYoR7+OGH3dChQ53P53NPPvlkUBv9+vVzderUcVdffbWbP3++O/fc\nc52ZuRtuuCGonpm5bt26ueTkZHfvvfe6e++91yUkJLjk5GQ3b948d+yxx7rZs2e7O++808XGxrr+\n/fsHbf/OO++42NhY16tXLzd79mw3Z84cd8IJJ7jY2Fj3ySefFNTLf/92797dDRs2zD388MPuqquu\ncj6fz912220F9Z5++mkXFxfnzjzzTPf000+7p59+2i1btsw5570PU1NTSzxfU6ZMcT6fr1KPqzro\nn5Li8kKfUF0euLNatizfyTpw65+UFL79lPK/t3JyckqULV++3JmZe+qppwrKrr/+eufz+dyKFSsK\nyrZu3eoSEhKcz+dz69evD9vmmDFjXMOGDd3+/fsLyvr06eN8Pp/7xz/+UVCWf+6vW7du0OvyzTff\ndGbmFi1aVO5jjYSU005zvPuuY8mSkrd333Ute/Z0Gbt2lfuW1KNH2PZTevWqUP8TEhLcuHHjQj62\nf/9+16xZM9ejRw938ODBgvInnnjCmVnQeTX//83FixcXlP3yyy+uQ4cOhzyvluUzkYhIWWVnO/d/\n/+fcP//p3LRpzo0e7dzppzvXvHnwf6GJiXkuJmZokTLvXAR0dxHIoepWTUwnInLkcc6Rm9uA0ocS\nG5s2xZOe7sLUKbV1IHzbubnxOOcq9FdjM+Pqq68O+dgVV1xR8HPjxo3p1KkT69atY9iwYQXlHTt2\nJCEhgW+++aagLCEhgVWrVrF27VrS0tLC7v8Pf/hD0P2xY8fy6quv8vbbb3PhhRcWlA8bNozExMSg\nuq+99hotWrTgoosuKiirU6cO48eP5+KLL+b9999n0KBBBY/95je/oUWLFgX3Tz75ZE499VT+85//\nMHPmzLD9rErOOXLr5Ib71bMpZxPpC9LL97LaR9i2c325FXpd/ec//+HKK6/k3nvvLSi76aabAMjN\nzeXOO+/k1FNP5Z133ikY5XT88cczcuRI2rRpU7DNggULWLt2Lc899xy//e1vAbjyyis5/vjjy9Uv\ngKSkJF599VUAxowZw5o1a5gxYwbXXHMNDz74YME+UlJSeOyxxxgxYgQAL774IkuWLOHuu+/mtttu\nA+Caa67hwgsvZM6cOYwdOzZoJNfXX3/NV199VXA8CQkJXH311UybNo01a9YQHx8PeNOd//KXv7Bh\nwwbatm1b0G7//v0L+gne6JMuXbowadIkXn/99aBjSk9P55FHHim4v3XrVv72t79xzz33AHDxxRdz\n9dVX065dOy6++OJyP3cVPa5oc87RIDc33Euf+E2bcOnp5ZoccugzNsTnlv+9FRsbW/DzgQMH2LVr\nF+3atSMhIYGVK1dyySWXAN55sUePHqSnpxfUb9q0KZdccgkPPfRQqW3u3r2bffv2cfrpp/PII4/w\n5ZdfctxxxxU83rBhw6Bzcv65v3Xr1px00kkF5aeeeipA0P8J0eacIzc2tnBkWHFmbDIjfcWK0uuE\n3wH4fGHbz61Xr0Ln1YSEBJYvX87mzZtJSkoKemzFihX8/PPPTJ8+PWjk6MUXX8z1118fVPe1114j\nKSmp4JwKEBcXx1VXXRVy5K2ISEXs2QPr1sGaNcG3tWth8+bCek2aQIcOkJYG/ft7P+ffT0w0UlP3\nkJVVnu9Th08BmohIhJgZMTF78L46hTqhO5KS9vDKK+U52RuDB+9h8+bS246J2VMpUy5CTeGKi4uj\nadOmQWWNGzemdevWJeo2btyY7du3F9y/6667OO+88+jYsSPHHnssAwcO5NJLLw36MgbelLB27doF\nlXXs2BGArKysoPKUlJQS+12/fj0dOnQoUd65c2eccyXWBgoV5nXs2JHnnnuuRHk0mRkxB2PCvaxI\nik3ilatfKVf7g18YzGa3udS2Yw7GVOh1VV2/6JlZwdTFfKeeeirLli0LKvf5fJx00klBU45fe+01\n6taty7hx44K2v/HGG3n++ed57bXXuPbaawvKzzrrrKAwMD9UGDZsWEHIVLT8m2++oW3btnz66aes\nWbOGO+64g59//rmgnnOO/v3789RTT5U4puIBeO/evfn3v//N7t27adiwYdmenDIq73FVB2bGnpiY\ncG8r9iQlYa+U731lwJ7Bg3GbN5fefkz531s5OTncfffdLFy4kI0bNxZMYzYzdu7cWVBv/fr19OjR\no8T2nTp1KlG2evVqJk6cyJIlS9i1a1fhsRRrEyj13F/09QDQqFEjgKD/E6LNzIjZt88LukI9/86R\nlJfHK0WCwMM1OC+PzWHaj9m3r0Ln1XvvvZdRo0bRpk0b0tPTGTRoEJdddhmpqamsX78eM6N9+/ZB\n29SpU6fE/53r168P+X9hqNeHiEhZ/PKLF4jlB2NFg7JNmwrrNW5cGIz17euFY/n3i33lKGHIkF7M\nm/dGYFmbyFKAJiISQeFO6D7f61xwwel0716+tocNC9/20KGnl6/hYurXr1+irE6dOiHrllae/2UO\nvC/w69at48UXX+TNN9/kb3/7G7Nnz2bBggUlAoyK9LE2G3LWEOZ9M4+89iUX/vat83HBwAvonlS+\nF9awAcPCtj30V0PL1W6+6vxFr3iY07hxY4ASIUDxUHj9+vW0bNmSBg0aBNXr3LlzweNFhWoPSoYQ\njRs3xjlXsK81a9YAcNlll4Xsv8/nY+fOnQXthTqmJk2aAF6AUdkBWnmPq7roNWQIb8ybx8AQC+q/\n7vNx+gUXUO4TNtBr2LDw7Q8t/3tr7NixLFq0iAkTJtCjRw8aN26MmfG73/0u5AUCDmXnzp2cccYZ\nJCQkMHXqVNq1a0dcXBwZGRncdtttJdqsyP8J1cGQM89k3iefeGuUFeP75BMu6NeP7n5/udsf1rdv\n2PaH9ulT7rbBW6v0jDPO4IUXXuDNN99k5syZTJ8+nRdeeKFC7YqIlEVOTsmRZPlh2fffF9bz+wtD\nsd69g0eSNWtWvkG+ANOm3cS7755PZqYjL+/oyjmoUihAExGJoOATev5i/w6f73U6d57N1KmLq2Xb\nkZaQkMDIkSMZOXIke/fupXfv3kyZMiUoQMvLy+Obb74JCkm++uorIPSIs+KSk5P5/PPPS5TnL6qc\nnJwcVJ4fThT19ddfl2lfVW3aHdN49+x3yXSZXtDl/erxrfPReW1nps6fWi3bhur9Re9wQoCKBADl\nDRvyQ4tZs2bRrVu3kHWLh2IVCTBKGxFz8ODBkOU1PUS5ado0zn/3XVyRhf4dXrg1u3NnFk+t2Gs/\nku0vXryYUaNGBU2N3rdvHzt27Aiql5ycHPJc9+WXXwbdf++999i+fTsvvvgivXr1Kihft25duftY\nnU374x95d/BgMoG8k0/2vsU5h++TT+j86qtMLefIw6pqH6B58+aMGTOGMWPGsHXrVk488USmTZvG\n9OnTcc6xdu1azjzzzIL6Bw8eJCsrK+hckpycHPLq08VfHyJy5Nm3D775JvR0y+++8wbxAjRsWBiK\n9exZGJJ16ABHHVX+kCwcv9/P0qWLmTRpFs8991rQ9M/KpqtwiohEUP4JfezY5aSknE2rVueSknI2\nY8cuZ+nSxfgr8BftSLYdSdu2bQu6Hx8fT1paGvv27StRN3/dqaL369WrR//+/Q+5n0GDBvHDDz/w\nj3/8o6Ds4MGDzJ07F7/fH/RFAuDf//43m4qMJf/4449Zvnx50Dpp1YXf72fpm0sZ23IsKS+n0OqV\nVqS8nMLYlmNZ+ubSir+uItR2vvwvev/617/49ttvadq0KdOmTSM5Obngi15R+V/0ikpOTg75ZT4a\nX/SSk5PZtGlTiSsLlhbWllf+yDy/30+/fv1C3koLq8IpLShr0qRJiQAGSk6hri38fj+Lly5l+dix\nnJ2SwrmtWnF2SgrLx45l8dKKv/Yj2X6dOnVKjAp74IEHSoSdgwYNYtmyZaxYsaKgbMuWLTzzzDMl\n2nPOBbW5f/9+5s+fX+4+Vmd+v5+lr7zC2J07SbnjDlrddRcpd9zB2J07WfrKK5Xyu49U+3l5eUFT\nbAGaNWtGy5Yt2bdvHyeffDJNmzbl0UcfDfp9PvXUUyVGgQ4aNIhNmzaxeHHhH+D27t3Lo48+Wu7+\niUjNsX8/fPklvPwyzJ4N114Lv/oVpKRA/frQpQucey5MngzLlkFiIlxyCfz1r/Df/3rrlu3aFXyF\nzFGjoFcvOProyIRn+fx+P3PmTOGVVx46dOUK0Ag0EZEIyz+hz5lDhRf1r8q2I6VLly706dOH9PR0\nEhMT+eSTT3j++ecZP358UL3Y2Fhef/11Ro0aVbCY/2uvvcbEiRNLrL8WylVXXcWCBQsYNWoUK1as\nICUlheeee46lS5cyZ86cEtPt0tLSOP3007nmmmvIyclhzpw5HHXUUdx8882VevyVxe/3M2f6HOYw\nJzKvqwi0nZeXx+7duwvWQYLSv+iNHj26YB200r7ovfXWWyxevJjzzz8fiN4XvUGDBvHII4/w4IMP\nBq2/Nnv2bHw+H+ecc06l7Cc9PZ327dszc+ZMhg8fXuI1vHXrVpo1a3bY7TZo0CBkUNa+fXt27tzJ\nF198wbHHHgvA5s2b+fe//12+A6gB/H4/U+bMgTmV/76KZPuDBw/mySefpFGjRnTp0oWlS5fyzjvv\nlHg93HLLLTz55JMMGDCA6667jvj4eB599FFSUlL47LPPCuqddtppNGnShMsuu6zg3PzUU0/ViP9j\nysvv9zNn2jTmEJn/TyPVfnZ2Nq1bt2bYsGF069aNhg0b8tZbb7FixQruu+8+6taty5QpUxg/fjx9\n+/blwgsvJCsri8cff5y0tLSgflx55ZU8+OCDXHrppaxYsYKkpCSefPLJEucaqTmfuUSKy82Fb78t\nOdVyzRpYvx7yc/b69QvXIbvoouDplklJkQ3DyiM7O5uJf57I8y89H9H9KEATEalCkfywVZUf5Erb\nV6hyMwsqv+6663jppZd466232LdvH8nJydx9990FV2LMV7duXV5//XXGjBnDLbfc4n3xnDKFO+64\nI2z7+eLi4nj//fe57bbbeOKJJ9i1axedOnVi4cKFXHrppSXqX3bZZfh8Pu6//35++uknTj31VObO\nnUvz5s3L9JxEU015XVXnL3oVmU44ZMgQ+vbty8SJE/n222/p1q0bb7zxBi+//DITJkwIeSGO8jAz\n/vrXvzJo0CC6du3K6NGjadWqFRs3bmTJkiU0btyYF1988bDbTU9P5+2332b27Nm0bNmS1NRUTjnl\nFC666CJuvfVWzjvvPMaPH8+ePXt4+OGH6dSpU9BFFGqrSJ9TK7P9Bx54gLp16/LMM8+Qk5PD6aef\nzttvv82AAQOC9tOiRQvee+89xo0bx/Tp02natCnXXHMNLVq04Pe//31BvcTERF599VVuvPFG7rjj\nDpo0acKll15Kv379GDBgQJmOpbRzc2nl1UlN+t3Hx8fzhz/8gTfffJMXXniBvLw80tLSeOihh7jq\nqquAwitaz5o1i5tvvpnjjjuOl156ieuuu464uLiCturXr8+7777LuHHjePDBB4mPj2fEiBEMHDiQ\ngQMjvzh3dZf/Bf3lt18mt04uMQdjGHLWEKbdMa3ajvqXI1NurheGhZpumZUF+YOT4+K8QCwtDYYN\nC55umZTkXUC4JsjOzqbn2T3JTMsk78w8+CqCO3PO1cgb0B1wGRkZTkQkGjIyMpzOQ5ExatQo5/f7\nq2RfWVlZzszcrFmzqmR/R7L9+/e7W2+91Z144omucePGzu/3uxNPPNEtWLAgqN6DDz7oUlNTXf36\n9d0pp5ziPvzwQ3fSSSe5QYMGBdX77rvv3HnnnecaNmzojj76aHfDDTe4N9980/l8Pvf++++XuV8L\nFy50Pp+vxHt5ypQpzufzuZ9//jmofNSoUa5Ro0ZBZXv27HE33nija926tYuNjXWdOnVy9913X4l9\n+Xw+N378+KCyrKws5/P5StR/7733nM/nc4sXLw4q/9///ueGDRvmjjrqKFe/fn2XmprqLrroIrdk\nyZJD9j3/WNevX19Q9tVXX7k+ffq4Bg0aOJ/P50aPHl3w2Ntvv+2OP/54FxcX5zp37uyeeeaZgrYr\n+7hEpOrk5eW5pk2buquuuqpS2qvtn4l27drluvbo6nwjfI7JOKbgmIzzXepzXXt0dbt27Yp2F+UI\nk5vr3Nq1zr32mnNz5zo3frxz55zjXFqac3XrOuetSuZcbKxzXbo4d+65zt14o3MPP+zcO+84t2GD\ncwcPRvsoKse4m8d5780pOK7C4S0x2t1FIIcyV80WcC0rM+sOZGRkZNC9AldEEhEpr5UrV5Keno7O\nQ5Vv9OjRLF68uMS6LpGwfv16UlNTmTlzJjfccEPE9yeHzznHUUcdxfnnn8+CBQui3R0RkRpl3759\nxMbGBpUtXLiQyy+/nGeeeYaLLrqowvuo7Z+Jxt8ynnmb55GXFuIK1Wt9jG05ljnT50ShZzWbcw6H\nK/g3VFl+XlG8LFz9ymwrmvUPHHT8+KPju+8c333v2LjJ8f33sHGjY/MPjoMHvayobowjKQlatnK0\nbOlo2cqRlOT93LQZ+Hw143jLW3/GmBnsuGCHd+GrTcAjAKQ75yp9uLymcIqIiEi1EeqL3qJFi9i2\nbRt9+/aNUq9ERGquZcuWMWHCBC644AKaNm1KRkYGjz32GMcffzzDhg2Ldveqve2/bOe5N54j7zcl\nwzOAvPZ5PPLsI3za+dMaETZUl/pSDg2BYwK3Ig4A3wVuAOwI3DKrrmvhGN7U/fx/Q5UZgfJiZYeq\nD7ArbxdU0coAEQvQzOwPwE1AC+B/wDjn3Cel1D0TWFKs2AFJzrmfItVHERGpvqp6TbfqvibPkaIy\nv+jl5OSwc+fOsHUSExOJiYmpSJdFRKq1lJQU2rZty9y5c9m2bRuJiYmMGjWKe+65h7p1NZ4i3/Zf\ntrN6y2pWbVnFqp9WsXrralb9tIrN2ZthH6V/QTewekZrf2t8Pl/pX/ojEB6ofuTrV0Zbzhk//Wh8\n9z18t8H4boOxYYOxYb3x/fdG7n6vpTo+o1UrIyXZaNvWSE6BlGQjNcVo2dKIqVuznruqkvr3VLJc\nVpWEaBE5Y5rZ74BZwFXAx8AE4A0z6+ic21rKZg7oCGQXFCg8ExE5Ij3++OM8/vjjVbKv5ORkDuav\npipRV5lf9P7xj38wevToUh83M5YsWcIZZ5xR0W6LiFRbycnJtfrquYer1KBs92YA6lgd0hLT6HJU\nF6448Qq6Ht2VG1+4kU1uU+gv6A6axzTn6fOfrtoDkWolLw82bQp9dct16yAnx6tXpw6kpHgL9Q8+\nGTpcXHi1y+Rk0N/0Dt+Qs4Yw75t55LUPPUq0MkXqTw4TgAXOuScAzGwM8GvgcuDeMNttcc5FfsEb\nERERqZYq84vewIEDefvtt8PW6datW6XsS0REqpfyBGVdjupCp6adiK0bvJTARwM+KvULum+dj6G/\nGlolxyTR5Rxs3hz66pZr18Ivv3j1fD4vDOvQAfr0gSuvLLy6ZUqKQrLKNu2Oabx79rtkukzy4iMb\nolV6gGZmMUA6cHd+mXPOmdnbQM9wmwKfmlkc8AUwxTn3UWX3T0RERI4MzZs3p3nz5tHuhoiIRFBl\nBmWlCfqC3j7P++bqvPCs89rOTJ0/NYJHKFXJOfjhh+ARZEWDsr17vXpmhSHZ6afD6NGFIVlqKtSr\nF93jOJL4/X6WvrmUSVMn8dxLz7GZzRHbVyRGoDUD6gA/Fiv/EehUyjabgauBFUAscCXwnpmd4pz7\nNAJ9FBERERERkRqiKoKy0hT9gv7Syy+R68slJi+GoWcNZer8qfj9/so4RKkizsFPP4Webrl2Leze\n7dUzgzZtvFDstNNg5MjC6Zbt2kFsxV5WUon8fj9zps9h5O9Gkp6eHrH9VItVI51zXwNfFylaZmbt\n8aaCjgy37YQJE2jcuHFQ2fDhwxk+fHil91NEREREREQiJ5pBWTj5X9DnMAfnnC4+VM05B1u3hh5F\ntmYNZGcX1m3d2gvFTjkFLrmkcCRZu3YQFxe9Y5Dwnn32WZ599tmgskNdPKqiIhGgbQUOAsXnTDQH\nfjiMdj4Geh2q0uzZs+nevfthNCsiUrkyM6vJNaJFREREoqA8n4Wqa1BWFgrPqgfn4OefS44iy79f\nNEtp1coLxbp3h9/9rjAka98e6teP3jFI+YUaOLVy5cqaNQLNOZdrZhlAf+AlAPPOMP2BBw6jqRMg\ngpNXRUQqqFmzZsTHxzNixIhod0VEREQkquLj42nWrFmJ8poclEn1sG1b6OmWa9bAjh2F9ZKSvFDs\nhBNg2LDgkKxBg+j1X2qPSE3hvA9YGAjSPsabihkPLAQws3uAls65kYH71wHfAquAOLw10PoCv4pQ\n/0REKqxt27ZkZmaydevWaHdFREREJKpiGsbwHd/xesbrCsrksO3YUfp0y23bCus1b+6FYsceC7/5\njfdzWpp3a9gwev2XI0NEAjTn3D/NrBlwF97UzU+BAc65LYEqLYA2RTapB8wCWgJ7gc+A/s65/0ai\nfyIilaVt27a0bds22t0QERERqRIaUSbltXNn6Ve3LPr36KOP9gKxY46BIUMKR5KlpYGu1yDRFLGL\nCDjn5gPzS3lsdLH7M4AZkeqLiIiIiIiIlJ2CMimP7OzSp1tu2VJYr1kzLxTr2BEGDQoOyYpdI1Ck\n2qgWV+EUERERERGRqqegTA7X7t2hF+1fswZ+/LGwXmJiYTA2YEBhQNahAyQkRK//IuWlAE1ERERE\nRKSWU1Amh2PPHli3ruR0yzVr4IcfCuslJBSGZP37B48kS0yMXv9FIkEBmoiIiIiISC2hoEzK6pdf\nCkeOFR9RtmlTYb3GjQuDsT59Cn/u0AGaNo1a90WqnAI0ERERERGRGkZBmZRFTk7JkWT5Ydn33xfW\n8/sLQ7HevYOnWzZrBmbROwaR6kIBmoiIiIiISDWloEwOZd8++Oab0NMtv/8enPPqNWxYGIr17Bk8\nkuyooxSSiRyKAjQREREREZEoU1Am4ezfXxiSFZ9uuWFDYUgWH18Yil1ySXBI1ry5QjKRilCAJiIi\nIiIiUkUUlNV8zjksAklUbi58+23o6Zbr10Nenlevfv3CkWQXXVT4c4cOkJSkkEwkUhSgiYiIiIiI\nVDIFZbVLdnY2EyfO5OWXPyQ3twExMXsYMqQX06bdhN/vL3M7ubleGBZquuX69XDwoFcvLg7at/dC\nsWHDgq9u2bIl+HwROlARKZUCNBERERERkXJSUFb7ZWdn07Pn+WRm3kBe3hTAAMe8eW/w7rvns3Tp\n4qAQ7cCBwpCs+HTLrCzvcYDYWC8kS0uD3/wmeLplq1YKyUSqGwVoIiIiIiIih6Cg7Mg1ceLMQHg2\nsEipkZc3kMxMx5AhszjhhCkFYdm333ojzQDq1YN27bxQbOjQ4OmWrVtDnTpROSQRKQcFaCIiIiIi\nIgGHCsp85iMtMY2uR3XlihOvoMtRXeh6dFcFZTXcgQOwYwds2wbbtwf/++STHwZGnpWUlzeQ99+/\nj82bvVBs0KDg6ZZt2yokE6ktFKCJiIiIiMgRR0FZ7eMc7NnjhV6hgrD8f0OV7doVus26dR15eQ3w\npm2GYrRqFc+XX0bmwgIiUn0oQBMRERERkVpLQVnNs3+/F2yVFoCFC8Ly1xcrLiEBmjSBxETv1rSp\nN0osv6zoY0XL4uONdu32kJXlCB2iOcpGCHEAACAASURBVGJi9ig8EzkCKEATEREREZEaT0FZ9eKc\nN6rrcAOw7dth9+7QbcbFlQy7OnUqGXoVD8IaN67YNMohQ3oxb94bxdZA8/h8rzN06Onlb1xEagwF\naCIiIiIiUmMoKKtaOTnlGwm2YwccPFiyPZ/PGw1WNORKSoIuXcIHYU2aQP36VX/8ANOm3cS7755P\nZqYLhGjeVTh9vtfp3Hk2U6cujk7HRKRKKUATEREREZFqR0FZ5Tl4EHbuPPyRYNu2wS+/hG6zQYOS\nIddxxx16SmSjRl6IVpP4/X6WLl3MpEmzeOml+8jNjScmZi9Dh/Zi6tTF+P3+aHdRRKqAOeei3Ydy\nMbPuQEZGRgbdu3ePdndERERERKQcDico63pU1yM2KHPOC7PKMyVyxw5v++Lq1AkfdoV7rF69qn8O\nqgvndMEAkepo5cqVpKenA6Q751ZWdvsagSYiIiIiIhGnEWWeAwe8QKs8Qdi+faHb9PtLhlwpKYcO\nxxo2BOVAh0/hmciRSQGaiIiIiIhUmiMhKHPOW+i+PFMid+0K3Wa9eiVDrvbtDz0SLCEBYmKq9vhF\nRI5ECtBEREREROSw1YagbP9+L9gqTxB24EDoNvMXyM8PuZo2hQ4dDj1NMj5eo8FERKozBWgiIiIi\nIlKq6h6UOeeN6jrcAGz7dm8UWShxcSXDrk6dDj0lsnFjb10xERGpfRSgiYiIiIhI1IOynJzyjQTb\nvh3y8kq25/N5wVbRkCspCbp0CR+ENWkC9etX+HBERKSWUYAmIiIiIlKNRPoKf5EMyg4ehJ07yxeE\n/fJL6DYbNCgZch133KGnRDZq5IVoIiIilUEBmoiIiIhIlGVnZzNx4kxefvlD9u+Pp169vQwZ0otp\n027C7/eXq83yBmUdEzuRlxsbFG59sw5WHCIA27bNC8+cK9mXOnVKhl1t2kC3bocOwurVq8gzKyIi\nUjkUoImIiIiIRFF2djannHIuX2b5of46iMuFnTHMfbQBb711Lh9//GLYEK0sQVnr+mm0ju3KqfWu\noHHDLsTv7kqd7Z3YtS6W7dthyTb4V5EgbP/+0Ptq1KhkyJWSEj4AS0yEhg21QL6IiNRsCtBERERE\nRKLo5pun8eXGb+C330GHPDDAAV9v4MtX2nD99XczefI9ZP2wnf9t8oKyNTtXseGX1fxwcBW7zQvK\ncD5i96RR5+euHNh8BXzfBbZ0JW9rJzYcjGVDYH/16pUMudq3P/RIsIQEiImJ0pMkIiISZQrQRERE\nRESi6Ol/PQ1DNkHHIivhG9ApD9jAYytn89gDi8AfCMryfLAtjZgdXWmw9wpSc7vQ3NeVVnGdOKpJ\nLE1aQGKX0oOw+HiNBhMRETlcCtBERERERKrQxo2wbBm8t2w7769exe46P3ojz0Lp6OCDXIZ3upwu\nR3flhJZdSU/pxNGJsdSpU7X9FhEROZIpQBMRERERiZCcHHhv+XZeXb6apetW8dW2VeyuvxqOXuWN\nKDsZWIc34iwUgzouhqd//+eIXplTREREwlOAJiIiIiJSCbbt3c7bn63mzf9bxYr1q/h292p2xa0q\nnHqZ5KNJizROTehKj/ZXcGqqd9XL0xeeQbbbGTpEcxBfJ07hmYiISJQpQBMREREROQz5V73M+G4V\n761exWebV/P9vlXsq1e4RllMbhot6nfltKOvoPcxXRjQvSvHNu9EbN3YEu1d/JuLWLBmAXQMsbOv\n4ZLfDo/sAYmIiMghKUATEREREQkhPyhbtWUVX/y0ihXrV7N6yyp25gUv5l93e1faxF3BCa260P+4\nrpzXuxOtmpcMykoz464Z/Pes//IlX+I6uIKrcNoa45h1x3Dvgnsjc4AiIiJSZgrQREREROSIVjQo\nW/XTKlZvXc3nP67ixz2BoMz58G1PI+/HrrDlCtrEduHklK6cnd6J3r+L5ZhjwOcr//79fj/L317O\npKmTeOnll8j15RKTF8PQs4Yy9eGp+P3+yjlQERERKTcFaCIiIv+fvXuPj6q+8z/+OpNMkplJCOGS\nhDsBwi14AQSJqKC1aCvEdtF6ASve7ZbWSnG3JEhluQnrpfArbbXsbu9ht+uuIqbY1ihlAyIF5aJB\nE+WmCChEGHKbJPP9/XEmmQwkkEAmk8v7+XjkMePMmcxnJJA57/l8P18R6RQaCsreO/Yen522gzIL\nBwk+Oyg7/fH98PlIulZlcNWwYUy8MpYJt8AVV0CXLi1fW0JCAiuXr2QlKzHGaOaZiIhIG6MATURE\nREQ6lPMFZQ7LQapzCJ6yDJyH7idmz0h8n2Tg+HIYQy+JZcIEmHA/TJgAgwZBa2dZCs9ERESazuv1\n8nRODn/67/8O6/MoQBMRERGRdqkpQdngpCH0js5glO9+Bnwykv3bMjiyZxiHa2Lp29cOySbcaV+O\nGQMuV4RflIiIiDSZ1+tlemYmcwoLyfL7uSKMz6UATURERETatKYEZUO6DSGjZwbTB9lLL098kEHR\nlmHs3B5LkQ/i4uzllzO/ChOegCuvhL59I/zCRERE5KI8nZPDnMJCbvL72RHm51KAJiIiIiJtQnOC\nsvtH38+ghJH4j2bw2e5h/P2vsWx+C44etb/X4MF2V9k9M+zLSy8FpzOCL05ERKSzMQaqqqCsDEpL\n7csW/io4cYInW+nlKEATERERkVbV3KBsZM+RjOiRgePEMHZsi+WtN+CVt2D3bvD7ISEBxo+HBx6w\nw7Irr4SePSP8IkVERNoyvx/Ky8MablFWBjU1TasnJgbc7sa/unWzW8fr3WZcLjxPPYV18mR4/18F\nKEATERERkbC4kKAsIzmDYd2HUeaN5e23Ycvf4Ndvwdat8OWX9kD/kSPtoGz2bPtyxAiIiorwixUR\nEWkJrdC1RVkZVFQ0rR7LOnewVRtune8Yj6fx+1wuiG5+PGUBpc8/jzl5ktbYfkcBmoiIiIhclIsJ\nymKjY6muhvfeg7c2w3NvwVtvwd699vfu3t0OyX74Q/ty3DhITIzgixURkc6rA3RtNTvcio1t/e2o\nm2HitGm8tno1N/n9YX8uyxgT9icJB8uyxgDbt2/fzpgxYyJdjoiIiEiH15ygLKNnxllBWa2jR+2Q\nrPZr2zb7PCQqCi67DDIzA7tjTrBnmbXh9+0iItIWtMeuraZ8haFrq6Op3YXzscJCkoO7cI41xrT4\nngL6vy0iIiIiIS62o6y+ykp4d3toYLZ/v31fr152WPbjH9th2dix9jmBiEhbZozBUrLfdB2xa+tc\nwVY76NrqSBISEnhxyxaemT+fP/3xj/DZZ2F7LnWgiYiIiHRSLdVRVssYOHgwNCzbsQN8PvtcYuzY\nYGfZhAn2+YnOL0SkPfB6vTydk0PBK6/gqaqi1Olk4rRpzF2yhISEhEiXd2E6YtfW+YItdW11aDt2\n7GDs2LGgDjQRERERuRAt2VFWX2kpbD+ju6z2g99Bg+yQ7K677MvLLrM/9BcRaW9ql4jNKSzkSb8f\nCzDAa6tXMz0/nxe3bGn5EE1dWyJtjgI0ERERkQ4iXEEZ2I0KRUWhYdmuXfa5l8cD48fDrFn2kswr\nr4Tk5FZ4wSIireDpnBzmFBaGDCm3gJv8fkxhIc888ghPzp7ddru2zrdDorq2RJpEfwtERERE2plw\nBmW1vvwS3n47GJZt3QonTtj3jRhhd5U98oh9mZFhbwAgItIuVVXBsWP219GjwcvA9YI//pEnG9nh\n7ya/n2f/8Af4wx/OvvNiu7bOF2ypa0ukVSlAExEREWmjWiMoA7uL7P337aBsyxb7srDQvi8pyQ7J\nHn3Uvhw/Hrp2DcerFRFpQadPNxqInXVZ++lAfV26QEoKJjkZD3bHWUMswN2zJyY/H6t+4KWuLZEO\nR3+jRURERCKstYKyWseO2R1ltd1lb79tn2tGRcGll8LkyfCjH9mBWXq6mhtEpA3w+6GkpOEQrKHb\nyspCH+9wQI8ekJJirzHv0wdGjw7+d0pK8HpyMsTFAXZAVpqWhtm/v8EQzQClHg/WqFHh/j8gIhGm\nAE1ERESklbR2UAb2Dpg7d4bOLvv4Y/u+1FQ7JHviCfty7Fh7xZCISKs4z9LJkMvPP4fq6tDHx8QE\ng6+UFBg5Eq677uxALCUFune/4LXmE6dN47XVq0NmoNXa4HBwdVbWBX1fEWlfFKCJiIiItLBIBGVg\nD/r/5JPQsGz7dqistM8zx4yBrCw7LJswAfr3V3eZiLSwFlo6WRd+DR7ccCCWnGwf2wr/iM1dsoTp\n+fmYwEYCtbtwbnA4eG7ECF5cvDjsNYhI5ClAExEREblAkQrKapWV2QFZ/cDs8GH7voED7ZDsW9+y\nLy+/3J41LSLSLBFaOtmWJCQk8OKWLTwzfz7PrluHu6qKMqeTiVlZvLh4MQkJCZEuUURagWWMiXQN\nF8SyrDHA9u3btzNmzJhIlyMiIiIdWHOCsoyeGS0elIHdXfbRR6Fh2c6d9oomt9se7l/bWXbllfby\nTBGRBrX00sn6XWEtuHSyrTLGYKl9V6TN2bFjB2PHjgUYa4zZ0dLfXx1oIiIiIgGR7iir7+RJ2LYt\nNDA7fty+b/hwOyh78EH7MiNDm72JdHqlpY2HYO106WRbpfBMpHPSWy0RERHpdNpSUAZQUwOFhaFh\n2fvv211nXbvaHWWzZ9th2fjx0K1bi5cgIm1NSy2drA2+2uHSSRGRtkQBmoiIiHRYbS0oq/XFF7B1\nqx2UbdkCb78NXq99vnvJJXD11TB3rh2YDR1q3y4iHUBjSycbCsYiuOukiIicTQGaiIiItHttNSgD\n+3x5167Q7rLiYvu+5GTIzITsbDssu+IKiI8Pazki0tK0dFJEpFNQgCYiIiLtRlsOymp9+mloWPb3\nv0NFBTid9uqpr3/dDs0mTIABA3QuLNLmaOmkiEi74vV6yVm2jP9+9dWwPo924RQREZE2py3setkU\n5eWwY0doYPbJJ/Z9/fsHd8WcMME+f9Z5skiEVFXZSyKb0immXSdFRNoNr9dL5tSpFN58M/7ERHjk\nEdAunCIiItLRtIeOslrGwL599syy2rDs3Xft82yXC8aNg7vussOyK6+E3r1btTyRziecSyfPDMa0\ndFJEpE3KWbbMDs/Gj4cPPwzrcylAExERkbBrT0FZLa8Xtm0L7S77/HP7vqFD7aDsvvvsy1Gj7CWa\nInIRapdOnmu5pJZOiohIPa9s3Ih/8eJWeS4FaCIiIp2QMQYrDN0U7TEoA/u8fe/e0LBszx676ywx\n0e4o+8537LBs/Hh7hZaINEFLL53UrpMiIp2SMYbDPh97Skt5r7SUPaWl7Dl9mv3Qah3CCtBEREQ6\nCa/XS86iHF756ytURVXhrHEy7YZpLHliCQkJCc36Xu01KKt1/Dhs3RoMy7ZuhVOn7Pdfo0bZQdkP\nfmBfDh9uN7aItJZwBdwt5lxLJ88Mxs61dLI2+NLSSRERqefYGUFZ7eXJmhoA3A4HIz0eRsXHU1xd\nTYkxrfK7QgGaiIhIJ+D1esmckknhkEL8WX6wAAOrP15N/pR8tvx5S4MhWnsPysBugNm9O7S7rKjI\nvq9nTzsk++d/ti/HjYNmZokiLcLr9fJ0Tg4Fr7yCp6qKUqeTidOmMXdJ8wPuZtPSSRERiYATVVW8\nVz8oKytjT2kpX1RVARBrWQx3uxnl8XBz9+6M8njI8HgYGBeHIxCYff8rX2H1tm32DLQw0y6cIiIi\nncD3/+n7rP5sNf4h/rPucxQ7eDD5Qe5+9O42v+tlU3z2WWhYtm2bvVtmdLR9Tl9/Z8y0NDW3SOR5\nvV6mZ2Yyp7CQG/3+2nyb1xwOnh0xghe3NBxwn5N2nRQRkTbCW13N+4FwrH5H2Wc+HwDRlsVQl6su\nIKu9HBwXR/R5lgG05i6cYQvQLMv6LjAXSAV2At8zxmxrwuMmAm8Cu40xjSZjCtBERESaLm1MGvuz\n9tudZ2cywG+Bb7evoAygogLeeSc0MDt40L6vb99gUJaZaYdnLldk6xVpyI+//30yV6/mJv/ZAfef\nHA62zp7NkytXBpdONqVTrClLJ88VjGnppIiINFNZTQ2FZWUhSy/fKy3lQGUlYL8NHXJmUOZ2M9Tt\nJuYi5mV4vV7mP/UUf3z1VT7buRPaU4BmWdbtwK+Bh4C3gceA24ChxpgvzvG4RGA7UASkKEATERG5\neMYY+o3vx6dTP230mKSXknjjT28wvMfwNhmUgT3Qf//+0LDsnXfsRpu4OLjiimBgduWVdoAm0h7c\nkJbGX/bvbzTfnhIdzV9iYs6/dPJcgZiWToqISAup9Pv5MNBRVjfQv7SUjysqqE2YBsbF1QVktWHZ\ncLcbVxg7lnfs2MHYsWMhTAFauGagPQY8b4z5DYBlWY8ANwP3ASvO8bhfAL8H/MAtYapNRESkU9l1\ndBcnTp2wz8QbOUNPtBK5LPWy1i7tnE6fhr//HbZsCQZmx47Z9w0ZYgdl3/62fXnppeB0RrZekfOq\nrITiYvjgA/tr717M3r14Dhxo8K8m2H9l3XFxmIULsVJTQ4MxLZ0UEZEwqvb7KSovtzvJ6gVmH5aV\nURM4pk9MDBkeD7f06FHXWTbS7SY+uuON3G/xV2RZlhMYCyytvc0YYyzL+iuQeY7H3QukATOAJ1q6\nLhERkc6m+EQxC95YQO6eXBIHJlL5UWXDM9A+cpD11awIVBjk98OHH4Z2l+3ebd+ekGB3lD30kB2W\njR9vD/8XaZOMsZdR1gvJ6q7v22f/UAN07QrDhmGNGEHphx9ivvyy0Q600h49sObMac1XISIinYjf\nGPZVVJy18+XesjJ8gVWLyU4nGR4PNyQl8WjfvnXdZV070SeY4YgEewBRwNEzbj8KDGvoAZZlpWMH\nblcbY/xtettuERGRNu6w9zCLNi5izTtrSPYk8/zU57n10Vu59mvXUkgh/sHBXTgdHzkYUTyCxT9b\n3Ko1njgBb78dDMu2boUvv7RHLo0cac8s+9737MBs+HA12UgbVFFxVjdZ3fWTJ+1jHA4YNAiGDYNv\nfMO+HDbM/qHu2bNuxtjE73+f1xqZgbbB4eDqrMgG3CIi0jEYYzhUWXlWUPZ+WRnlgd9BSdHRZHg8\nXJWYyIO9etV1lfWMiYlw9ZEX8Z46y7Ic2Ms2f2yM+aj25qY+/rHHHiMxMTHktjvvvJM777yz5YoU\nERFpB0rKS1hesJxVW1cRFx3H0uuXMnv8bFxOe3L+lj9vYf7i+ax7ZR1VjiqcfidZN2Sx+GeLm7/D\nXzNUV8OePaHdZR98YN/Xvbsdkv3wh/bluHFwxq91kcip7SarH47VXt+/P9hNlpRkB2MjR8I3vxkM\nyQYPtnezPI+5S5YwPT8fU1jITfV24dzgcPDciBG8uLh1A24REWnfjDEc8flCg7LAcH9vjb34Mj4q\nigy3m8vj45mRklIXlPWKiaE9NDXl5uaSm5sbctvJ2g+wwqTFNxEILOEsA6YbY9bVu/1XQKIx5ptn\nHJ8IlADVBIMzR+B6NTDFGPNmA8+jTQRERESAUl8pq7auYsXmFfhqfDw24THmXjWXrnFdG32MMSZs\nb46OHAkNy7Zts2efR0fDZZcFB/1PmGDnC+3gPZp0dLXdZA0FZadO2cdERQW7yYYPD+0m69Hjon+Q\nvV4vz8yfT8G6dbirqihzOpmYlcUPF4c34BYRkfbtc5/vrBlle0pLKamuBsDlcDDC7Q7d+dLjoX9s\nbLsIypqj3W0iYIypsixrO/AVYB2AZf+pfAVY1cBDTgGjzrjtu8B1wHRgf0vXKCIi0hH4anys2bGG\nRX9bxPGy4zw89mFyrs0hNT71vI9tqTdMlZXw7ruhgdn+/fZ9vXvbSzEXLrTDsjFjwO1ukacVaT5j\n7HS3sW6y2g+Vu3Wzg7FRo2D69GBQ1sRusguVkJDAkytXwsqVYQ24RUSkffqyqqqui6x+UHasqgoA\np2UxPBCU3ditW92MsjSXiyj9TmkR4VrC+Szwq0CQ9jb2rpxu4FcAlmUtA3obY+4xdgvc+/UfbFnW\nMaDCGFMYpvpERETaLb/xk7s7lwVvLmBfyT5mXjqThZMXkpaU1uTvcSEn6MbAwYOhYdmOHeDzQWws\njB0L//APdmg2YQL07dvcVybSAioqoKio4aDM67WPiYqyA7Fhw+DWW8/uJoswhWciIp3X6epq3m8g\nKPvU5wPsgfPpgaDsO71713WUDXG5cDockS2+gwtLgGaM+S/LsnoA/wKkAO8CNxpjPg8ckgr0C8dz\ni4iIdFTGGPKK8sjOz2bX0V1kDcvipdtf4pKUS5r0eK/XS07O07zySgFVVR6czlKmTZvIkiVzG1wi\nVloKf/97aGB25Ih936BBdkh211325WWXhbU5RySUMfDZZ2cP79+7Fw4cCO0mGz4cLrkEbrstGJQN\nGqQfWBERiajymhr21g/KAksw91dUAPZMq0FxcYzyeLgnNbUuKBvmdhOroCwiWnwGWmvRDDQREelM\nNh3YxLzX51FwqIBrB1zLU195isx+mU1+vNfrJTNzOoWFc/D7b6R2G06H4zVGjHiWzZtf5MiRBN56\nC7ZsscOy3buhpgbi42H8+ODcsiuvhOTksL1UkaDycrub7MygrH43WXR0sJvszPlkbaCbTEREOjef\n38+HZWVnzSj7qLyc2r2X+8fGnjWjbITbjVvbkDdLu5uBJiIiIi1n55GdZOdnk1eUx+jU0fxpxp+4\ncfCNzV7ilZPzdCA8u6nerRZ+/028956hZ89n8PmeBOyNBCdMgH/8R/ty5Eh7xZtIWBgDhw833E12\n8GCwm6xHDzsUu/RS+Na3QrvJnM7IvgYREen0qv1+PqqoOGvp5Yfl5VQHfpf1iolhlMfDzd27180o\nG+nx0CVa0Ux7oD8lERGRNqj4RDEL3lhA7p5c0ruls3b6Wm7LuA2H1fSW/ZIS2LfPno/+u98V4Pc/\n2ciRN+F2P8v69TBuHHRtfPNOkQtXVtZ4N9np0/Yx0dEwZIgdjN1+e2g3Wffuka1fREQE8BvD/gaC\nsr1lZVQGgrIeTiejPB6u69qV7/XpQ0agq6ybPvBp1xSgiYiItCGHvYdZtHERa95ZQ7InmeenPs+9\nl9+LM+rsN1ynTwcDsn37Qq/v3w8nT9YeaQAP9rLNhlh4PG5uuEE7/8lFMgY+/fTs4f0ffGDPJqvV\no4cdjl1+eWhQlpambjIREWkTjDF8Ull51oyy90tLKfPbiy8To6IY5fFwZZcu3N+rV90SzGTN2eyQ\nFKCJiIi0ASXlJSwvWM6qrauIi45j6fVLeeDS2Rz91MXrfzk7INu3D44fDz4+NhYGDrTzh8xMe7h/\nWlrtbRbjxpWyf7+h4RDN4HSWKjyTpisrgw8/PDso+/DDYDeZ02nPJhs+HO64I3Q+Wbduka1fREQk\nwBjDUZ/vrBll75WWcqqmBgCPw0GGx8MlHg93JifXBWW9Y2L0/qkTUYAmIiISIVVVsPfjUn6yZRVr\nD66gyu9j6Ik5uN+dy7M/6co/HQkeGx0N/fvbodhll8E3vlE/IIOUFDjXhkzTpk1k9erXzpiBZnM4\nNpCVdXXLv0Bp34yBTz5puJvs4MHgcT172sHYmDFw552h3WSa6SIiIm3I8aqqs5ZevldayvHqagBi\nLYuRgeWWt/ToQYbbzSiPh/5xcTgUlHV6elcjIiISJjU19mq2hpZYfnzAx6cpazDXLAL3cdj+ML2L\nc+iemkraIPj69aEBWZ8+FzfIf8mSueTnT6ew0ARCtNpdODcwYsRzLF78You8ZmmHSksb7yYrLbWP\ncTrt2WTDh9vtjfW7yZKSIlu/iIjIGU5WV/P+mUFZWRlHfD4AnJbFMLebDLebryYl1XWUDXK5iFJQ\nJo1QgCYiInKBjIEjR86ePVYblh08CIEPNAFITYWBaX6sS3I5fd0CsPZxQ8+Z5ExcyFXz0wjnuIyE\nhAS2bHmR+fOfYd26Z6mqcuN0lpGVNZHFi18kISEhfE8ukef322numbtcfvABHDoUPC452Q7FrrgC\nZswIBmUDB6qbTERE2pzSmhoKz5hR9l5pKYcqKwFwAOkuFxkeDw/Vm1GW7nLhPFfrvkgD9E5IRESk\nEcbYc8Ya6iDbt8+eiV5RETy+e/dg19iYMaEdZP37G974JI/s/Gx2Hd1F1rAsFl/3EpekXNJqrych\nIYGVK59k5Up73odmdnRAp0+HdpPVBmUffmjPLQOIiQnudDlzZnCXS3WTiYhIG1VRU8MH5eVnLb3c\nV1GBCRwzKC6ODI+HmSkpdUHZMJeLuItp4RepRwGaiIh0aidPNh6Q7d8fnIcO0KVLMBT72tdCA7KB\nA6GxJq5NBzbxwNp5FBwq4NoB17L5vs1k9ssM90s7J4Vn7Zjfb88ma6ib7JNPgselpNih2PjxcPfd\nwW6yAQPUTSYiIm1Sld9PUQNBWVF5Of7AMf1iY8nwePiHnj3rZpSN8HjwKCiTMNO7JxER6dBKS+1O\nscYCspKS4LEuVzAMmzQJZs0KBmRpadC1KzQnd9p5ZCfZ+dnkFeUxOnU0f5rxJ24cfKPCK2ma2m6y\nM4OyDz+E8nL7mJgYSE+3w7Fvfzu0m6xr18jWLyIi0ogaY/j4zKCsrIwPysqoMnZPWWpMDBluNzd1\n68YPAx1lIz0eEvUhkESIfvJERKRdq6y0A7KGZpDt3w/HjgWPjYmxm28GDoRx4+Bb3woNyHr2bF5A\n1pjiE8UseGMBuXtySe+Wztrpa7kt4zYclmZtyBn8fnsG2Zm7XO7da88sq5WaaodiV14J99wTDMkG\nDry43SVERETCyG8MBysqzppRVlhWRoXf7inrFh3NKI+HaxMT+U7v3owK7ILZ3emMcPUioRSgiYhI\nm1ZdbecLjQVkhw/bs8rAzhH69bMzhYwMmDo1NCDr1QvCOS/2sPcwizYuYs07a0j2JPPC1BeYdfks\nnFF6A9jpeb1nd5PV7nRZ200WGxvsJrvnnuAul8OGQWJiZOsXERE5B2MMh32+s5ZevldaSmkgKOsS\nFUWGx8MVCQnck5pqB2VuNykxB42BawAAIABJREFUMerOl3ZBAZqIiESU32+HYI0FZIcOQU2Nfaxl\nQe/ewVDs+utDA7K+fSMz2qmkvITlBctZtXUVcdFxLL1+KbPHz8bldLV+MRI5fr+99WpD3WSHDweP\n69XLDsUmTLDXCdeGZAMGqJtMRETavGMNBGV7Sks5GXjD5nY4GBlYcnlbz551HWV9Y2MVlEm7pgBN\nRETCyhh7GWVjAdmBA+DzBY9PTg6GYhMmhA7pHzDAbtJpK0p9pazauooVm1fgq/ExJ3MOc6+aS9c4\nzZ7q0Lzes4f313aT1W7LGhsLQ4fawdi99wa7yYYOVTeZiIi0Cyeqquq6yOovwfyiqgqAWMtieGCI\n/83du9cFZQPj4nAoKJMOSAGaiIhcFGPsQfyNBWT790NZWfD4pKRgKJaVFdpBNmAAeDyReBXN46vx\nsWbHGhb9bRHHy47z8NiHybk2h9T41EiXJi2lpibYTXZmUHZmN9nw4XDVVaFBWf/+6iYTEZF2wVtd\nbQdl9WaU7Skt5bPAJ5zRlsVQl4tRHg/f69OnLigbHBdHdDhnY4i0MQrQRETkvLzexgOyffvg1Kng\nsR5PMBC74YbQDrK0tPbdfOM3fnJ357LgzQXsK9nHzEtnsnDyQtKS0iJdmlyoU6caDsmKioLdZHFx\nwW6yiRPty+HD7du6dIls/SIiIk1UVlNDYVnZWUsvD1ZWAmABQwJB2f29etXNKBvqdhOjoExEAZqI\niNgzzA8caDwgO348eGxsbDAMu+oquOuu0ICse/eW2cmyLTHGkFeUR3Z+NruO7iJrWBYv3f4Sl6Rc\nEunSpClqauwf8IaCss8+Cx7Xu7cdjF19Ndx/f2g3mU4cRESknaj0+/mggaDs44oKAvsuMTAujlEe\nD3cmJ5MRmFc23O3Gpe5pkUYpQBMR6QR8PnsYf2MB2ZEjwWOjo+28IC0NLr8cvvGN0IAsJaVzZQmb\nDmxi3uvzKDhUwLUDrmXzfZvJ7JcZ6bKkISdPhu5wWRuUFRVB4NP1um6y4cPhmmtCu8kSEiJbv4iI\nSDNU+/0UlZefNaOsqKyMwP5L9ImJIcPj4ZYePeqWXo50u4mPxK5LIu2c/taIiHQANTXw6aeNB2Sf\nfmpvEAh2d1jfvnYYNnQoTJkSGpD16aPRTQA7j+wkOz+bvKI8RqeO5k8z/sSNg2/U7lGRVlNj/2A3\n1E1WPwnu08cOx669Fh58MBiU9evXuRJgERFp92qMYV95+Vkzyj4oK8Nn7J6yZKeTDI+HryYl8YO+\nfeuWX3Z1OiNcvUjHoQBNRKQd8Pvh6NGzg7Hay4MHobo6eHxqanAO2dVXhwZk/fpBTEyEXkg7UHyi\nmAVvLCB3Ty7p3dJZO30tt2XchsNS6NKqvvyy4W6y4uJgN5nLFewmmzTJDslqd7pUN5mIiLQzxhgO\nVlaetfSysKyM8sAnoUnR0WR4PExMTOSh2jllHg899eZOJOwUoImItAHG2HPGGusgO3AgOM8c7Dlj\ntQHZmDGhAdmAAXauIM1z2HuYRRsXseadNSR7knlh6gvMunwWzih9chs2td1k9bvIaq8fPRo8rm9f\nOxibPBkefjjYTda3r7rJRESk1RljLqoj3RjDZz7fWUHZ+2VleGvsxZfxUVFkuN2Mjo9nZkpKXVDW\nKyZG3fAiEaIATUSklZw82XhAtn8/nD4dPLZLl2Ao9rWvhQZkAwequaYllZSXsLxgOau2riIuOo6l\n1y9l9vjZuJxKIVtMSUloN1ltUFZcbA/oA3C7gztdXnddaDdZfHxk6xcRkU7P6/WSs2wZr2zcSFVs\nLM7KSqZNmsSSefNIOMcbs88DQVnt8svawKwksHTA5XAwwu1mlMfDP/TsWReU9Y+NVVAm0sYoQBMR\naSGlpXYQ1lBAtm+fvSKtlssVDMMmTYJZs4IBWVoadO3a8XaybGtKfaWs2rqKFZtX4KvxMSdzDnOv\nmkvXuK6RLq1VXOyn52eprm68m+zYseBx/foFQ7LvfCcYlKmbTERE2iiv10vm1KkU3nwz/sWL7Tdp\nxrB62zbyp05ly/r11MTFhcwoq+0qO1ZVBUCMZTEsEJTd1K1b3YyyNJeLKL3pE2kXFKCJiDRRZaW9\nlLKhGWT79sHnnwePjYmxl1KmpcG4cfCtb4UGZD17KiCLFF+NjzU71rDob4s4Xnach8c+TM61OaTG\np0a6tLDzer08nZNDwSuv4KmqotTpZOK0acxdsuScn56HqO0mOzMoKy6GwEkCbncwGPvKV0K7yTye\n8L1AERGRMMhZtswOz8aPD95oWfjHj+c9Y+j16KOUfvvbAEQB6YGg7Du9e9d1lA1xuXDqgyKRdk0B\nmohIQHU1HDrUeEB2+HDw2Kgou5Fm4EDIyICpU0MDsl691EzT1viNn9zduSx4cwH7SvYx89KZLJy8\nkLSktEiX1iq8Xi/TMzOZU1jIk34/FmCA11avZnp+Pi9u2RIM0aqr7R/6hoKy+klx//7BkOy73w0G\nZX366C+AiIiEnTGGSr+fMr+fcr+f8poa+9Lvp6ze9dr7LvS4I6+9hv/ppxsuYvx4ov/3f/nDiBFk\neDwMc7uJ1e9AkQ5JAZqIdBp+vx2CNRaQffKJPdMc7O6w3r2Dodj114cGZH37QrT+BW0XjDHkFeWR\nnZ/NrqO7yBqWxUu3v8QlKZdEurRW9XRODnMKC7kpsIsXgAXc5PdjCgt55rrreLJfv+BOl7XdZB5P\naDfZ8OH29fR0dZOJiEgIYww+Y8IWZJ15XIXfj2lGfXEOB67Alzsqqu66y+HAFRWF2+Gge3Q0rjPu\ney4+nlONLR2wLOLdbu5ITtbMMpEOTqd/IhIWLT5fqUnPaY9aaiwgO3gwOK8cIDk5GIpNmBAakPXv\nD7GxrVq+hMGmA5uY9/o8Cg4VMGnAJDbft5nMfpmRLqtxxtg/pJWV9rarF3rZwG0FL73Ek/XCs/pu\n8vt59t137e1db7gBZs8O7SbTCYGISLtV1QpBVv3jmhNoxVhWo0FW7fWu0dHnDLxqr58vGIt1OHBc\n4O+zX1dXc8qYhn8fGoOzslLhmUgnoABNRFqM1+slJ+dpXnmlgKoqD05nKdOmTWTJkrlNn690DsbY\n45caC8j274fy8uDxSUnBUOyWW0IDsgED1DzTke08spPs/GzyivIYnTqaDTM2MGXwlMbf3Bpjd1yd\nJ4S6mACryZcXIioK4uLs1Lf+ZeC6iY3FU1NDY2/tLcCdmorZsEEnACIiYVZdP3QKY5BVe72mGbU5\nLeu8AVVyTMxFBVm11+McjnYzPH/apEms3rYtdAZagGPbNrImT279okSk1SlAE5EW4fV6ycycTmHh\nHPz+JyEwYWn16tfIz5/Oli0vNilE83rPHZCdOhU81uMJBmJf/WpoQDZwICQmhuGFSstqKLi6iDDq\ny5PHeGf/Fj79/GO+54jnl4mj6RXTDet3i6HyiVYPrkIuPZ6Gb2/ssqnHxsaedz2xBZSmpWH2728w\nRDNAqdOp8EykjYhEF3dn5jemVYKs2turTNN7tKKgLpRynxFQ1YZU3Z3OkPCqseNcZ4RcDR0Xrdld\nDVoybx75U6dSCPjHjavbhdOxbRsjXn2VxevXR7pEEWkFCtBEpEXk5DwdCM9uCtxiAAu//yYKCw3z\n5z/DypVPUl5uB2GNBWTHjwe/Z2xsMBSbOBFmzAgNyLp318qyC9aU4Kolu6rCHFxVx0TzeY2XI9Ul\ndIlxMqzHUFK7D8ThcjU9sApDcNWWTJw2jddWrw6ZgVZrg8PB1VlZEahKRGp5vV5yli3jlY0bqYqN\nxVlZybRJk1gyb16LdHG3J35jqGiFIKv2OF8zAi0LzhtQJUZHk3qRQVbtcdq1sW1ISEhgy/r1zH/q\nKdY98QRVMTE4fT6yJk1i8fr1ne7vqEhnZZlm/MJoSyzLGgNs3759O2PGjIl0OSKdXlraDezf/z8k\nMp/uvEISVZTg5DjTOMliYmKm063bXzhyJPiY6Gh71lj9UKz+ZUpKB9zI70KCq3AFWBeiOR1XrRBc\nlZSXsLxgOau2riIuOo55V89j9vjZuJyuFvxD6xhqd+F8LLCRQO0unBscDp4bMSJ0F04RaVVer5fM\nqVMpvPnmBrtbtkT4BL12p8PWGApfOxi+OS4moGrucTGWpe5AUZeoSBu1Y8cOxo4dCzDWGLOjpb9/\n+/noXETaLGMMlZWx9OIqfkkhXyd4cv4qq3mIfL6MGsBDDxkGDbLqArI+few8ppWKtIOrSM+3ao3g\nqlu3Dt9xVeorZdXWVazYvAJfjY85mXOYe9VcusZ1jXRpbVZCQgIvbtnCM/Pn8+y6dbirqihzOpmY\nlcWLixcrPBOJoJxly+zwrP58JcvCP348hcD8p55i5ZIldXcZY6gKLDsMCZ8C18vOCKgaOq45gVdz\ndzqMPXMwfAMBVbeGBsNfQOAV63AoyJBWp585kc5JHWgi0iL6J/Tj56cPczNnf2r8Cg5+EJ/KRx+/\n2zIh1IV+jwv5966NdVx1dr4aH2t2rGHR3xZxvOw4D499mJxrc0iNT410ae2OPj0XiSxjDCXV1Ryq\nrGTKV7/KsaVLG93hL/qf/oneq1aFBGPN6dGKqR0MH4aOrDOPi7uInQ5FREQuhjrQRKTNO3QIXOVe\nvt7I2/mp+Fl1+jAkJzf9m6rjSurxGz+5u3NZ8OYC9pXsY+alM1k4eSFpSWmRLq3dUngmEj71w7FP\nAl+HKirsy3q3lfn99oc7DkfjQz0tiziXi7tTUkLCq6YGXq6oqHaz06GIiEhbpjNDEbkoL78M995r\nGGLcWJxs8BgLcCUlYf7jP7CaEmApuJIAYwx5RXlk52ez6+gusoZl8dLtL3FJyiWRLk1EOqlmhWMB\nUUDv2Fj6xsbSLzaWy+Pj6673jY3lNmP4xJhGO9B61NSweNCg1nuRIiIichadoYrIBamogMcfh5/+\nFL51cxlfbPRiTtth2ZkMUJaYiHXLLa1dprRjmw5sYt7r8yg4VMCkAZPYfN9mMvtlRrosEenAwhGO\n9YuLI8XpJPocu+J8c/JkVm/bFjoDLcCxbRtZkyeH4dWKiIhIcyhAE5Fm++ADuP122LsX/mvu29z6\n8kyeLC/nNcvipgbmjG1wOLg6KysClUp7tPPITrLzs8krymN06mg2zNjAlMFTtORQRC5KpMKxplgy\nbx75U6dSCA3uwrl4/fqLe/EiIiJy0RSgiUiTGQO/+hXMng0D+1az/76lpD73LzBmDHPffpvp3/42\nprCQm/zBXTg3OBw8N2IELy5eHOHqpa0rPlHMgjcWkLsnl/Ru6aydvpbbMm7DYV3ciamIdHy14Vj9\nMKythGNNkZCQwJb165n/1FOse+IJqmJicPp8ZE2axOL167VLroiISBugAE1EmuTUKfjOd+APf4Af\n3VrM4oN3E/X82zB/PsyfT4LTyYtbtvDM/Pk8u24d7qoqypxOJmZl8eLixXrzL4067D3Moo2LWPPO\nGpI9ybww9QVmXT4LZ5Qz0qWJSBvQ3sOxpkpISGDlkiWsRLvkioiItEUK0ETkvP7+d7jjDjh21LD1\ngTWMz30MUlOhoAAmTKg7LiEhgSdXroSVK/XmX86rpLyE5QXLWbV1FXHRcSy9fimzx8/G5XRFujQR\naSWdJRxrLv3+FBERaXsUoIlIo/x+eO45mDcPJo88xs6BD+JZsw4eeMC+Iz6+0cfqzb80ptRXyqqt\nq1ixeQW+Gh9zMucw96q5dI3rGunSRKQFKRwTERGRjkQBmog06NgxuOce2LAB/u2b67m34H6swwZe\nfhm0IYBcAF+NjzU71rDob4s4Xnach8c+TM61OaTGp0a6NBFpJoVjIiIi0tkoQBORs7z+OsycCbHV\npRz82hz6/e8LcPPN8G//BikpkS5P2hm/8ZO7O5cFby5gX8k+Zl46k4WTF5KWlBbp0kSkAQrHRERE\nRM6mAE1E6lRVwZNPwrJl8I9jt/KT4zOJ3ngYfvELeOgh0LJMaQZjDHlFeWTnZ7Pr6C6yhmXx8h0v\nMyp5VKRLE+m0FI6JiIiIXBgFaCICwP79cNddsH1rNRuvW8zVGxdjjR0LG16FoUMjXZ60M5sObGLe\n6/MoOFTApAGT2HzfZjL7ZUa6LJEOTeGYiIiISPgoQBMRXnwR7r8fLvcU8cXwmSRs3A7z50NODjid\nkS5P2pGdR3aSnZ9NXlEeo1NHs2HGBqYMnqJNJUQuksIxERERkchSgCbSiZWXw2OPwfPPG34x5gUe\n2jsHy90bCgrgyisjXZ60I8UnilnwxgJy9+SS3i2dtdPXclvGbTgsnZiLnM+5wrH6t50vHKsNxhSO\niYiIiLQ8BWgindR778Edd8CpoqPsv+QBBuxYb885e+YZiI+PdHnSThz2HmbRxkWseWcNyZ5kXpj6\nArMun4UzSp2LItAy4dhlDYRjqTExRKmzU0RERKTVKEAT6WSMgV/+En7wA7ivxzp+4nmA6KMWrFsH\n06ZFujxpJ0rKS1hesJxVW1cRFx3H0uuXMnv8bFxOV6RLE2k1CsdEREREOg8FaCKdyJdf2k1meX88\nzZ+HP8bVe9fYodmaNZCcHOnypB0o9ZWyausqVmxega/Gx5zMOcy9ai5d47pGujSRFqVwTERERETq\nU4Am0km89RbceScM+XwLR1LuJv7QEXjhBXjgAdDJnJyHr8bHmh1rWPS3RRwvO87DYx8m59ocUuNT\nI12aSLM1FI41NJRf4ZiIiIiI1FKAJtLB+f2wYgU8mVPFz3ot4t7yJVijxsHvNsCQIZEuT9o4v/GT\nuzuXBW8uYF/JPmZeOpOFkxeSlpQW6dJEGqRwTERERETCQQGaSAd25AjcfTcc/OuHFPWaSd8jO7B+\n/GPIzoZo/fWXxhljyCvKIzs/m11Hd5E1LIuX73iZUcmjIl2adGIKx0REREQkUnQGLdJBvfYafPtu\nw6zK59kQO4eo+L7w0mYYPz7SpUkbt+nAJua9Po+CQwVMGjCJzfdtJrNfZqTLkg5O4ZiIiIiItGUK\n0EQ6GJ8P5s+H3/zrEdb1fIArT70KjzwCTz8NHk+ky5M2bOeRnWTnZ5NXlMfo1NFsmLGBKYOnYCl8\n6JCMMa32Z1s/HGtoKL/CMRERERFp6xSgiXQgH38Md9wBfbe/zMeeB3BZDli/Hm6+OdKlSRtWfKKY\nBW8sIHdPLund0lk7fS23ZdyGw3JEujRpYV6vl5xly3hl40aqYmNxVlYybdIklsybR0JCwgV9T4Vj\nIiIiItIZKEAT6SDWroU5D3p5znqM2/3/BjfcAr/8JfTsGenSpI067D3Moo2LWPPOGpI9ybww9QVm\nXT4LZ5Qz0qVJGHi9XjKnTqXw5pvxL15s775rDKu3bSN/6lS2rF9/VoimcExERERExKYATaSdKy2F\n738f3v/3LbwTP5Nk/1FYswbuu88+QRY5Q0l5CcsLlrNq6yriouNYev1SZo+fjcvpinRpEkY5y5bZ\n4Vn9OYiWhX/8eAqN4ZYnnmDio48qHBMRERERaYACNJF2bNcumPGtKmZ89C/80lqKdcmVWL/9Mwwe\nHOnSpA0q9ZWyausqVmxega/Gx5zMOcy9ai5d47pGujQJkxpjOFhRQVF5Ob/Pz8e/bFmDx/nHj+eN\nxx+n+PbbFY6JiIiIiDRAAZpIO2QM/Pzn8PMffEBu9EwyzDtY/7IQfvQjiNZfawnlq/GxZscaFv1t\nEcfLjvPIFY+Qc00OKfEpkS5NWkCNMXxSWUlRWRlF5eV1X8Xl5XxcXo7PGPsfjaioxrtSLYs+Xbpw\nYMIEbRohIiIiItIAnWmLtDMnTsAD9xtSX/o526PnEt23H9bvt8C4cZEuTdoYv/GTuzuXBW8uYF/J\nPmZeOpOFkxeSlpQW6dKkmfyBkKy4NiCrF5Z9XF5OpTEARFsWaXFxpLtc3JiURHqfPqS7XKS7XFwH\nHDCm4RDNGJyVlQrPREREREQaoQBNpB35v/+DR28/wlPH7uOr/Ake/A7867+CxxPp0qQNMcaQV5RH\ndn42u47uImtYFi/f8TKjkkdFujQ5B78xHK6sDOkgqw3LPqqooCIwiywKSAuEYjckJZHeu7cdkrnd\nDIiNJdrR8O6pWZMmsXrbttAZaAGObdvImjw5jK9ORERERKR9U4Am0g7U1MDSpfDuj/+X16MeJCEp\nGn71Knz965EuTdqYTQc2Me/1eRQcKmDSgElsvm8zmf0yI12WBBhj+MznO6uLrDjwVR4IyRzAwEAn\n2XVJSTzkcjEkEJoNjIvD2UhIdi5L5s0jf+pUCgH/uHF1u3A6tm1jxKuvsnj9+pZ9sSIiIiIiHYgC\nNJE27tNP4cE7vNz2f4/yBP+B/+Zv4PjlC9CzZ6RLkzZk55GdZOdnk1eUx+jU0WyYsYEpg6doSV4E\nGGM44vMFO8jqhWXF5eV1u1o6gP6BkOyaxETuS00l3e2uC8liLiAkO5eEhAS2rF/P/KeeYt0TT1AV\nE4PT5yNr0iQWr19PQkJCiz6fiIiIiEhHogBNpA1bvx5+NqOAn5feTR/X5/DTf8Nx772NDwKXTqf4\nRDEL3lhA7p5c0ruls3b6Wm7LuA2H1bLhi4QyxnCsqiokGKvfTXa6pgYAC+gfG0u6281ViYnck5pa\nN5MszeUitoVDsvNJSEhg5ZIlrAy8BgWsIiIiIiJNE7YAzbKs7wJzgVRgJ/A9Y8y2Ro6dCCwHhgNu\n4ADwvDHmJ+GqT6Qtq6yE7Lk+uv10Ia/wFP5xE4he+1cYNCjSpUkbcdh7mEUbF7HmnTUke5J5YeoL\nzLp8Fs4oZ6RL6zCMMXxRVdVgF1lReTneQEgG0C82lnSXiysTEpiRnFzXSTYoLo64qKgIvorGKTwT\nEREREWm6sARolmXdDjwDPAS8DTwGvGZZ1lBjzBcNPKQU+H/ArsD1q4EXLMs6bYxZE44aRdqqoiL4\n0S2F5OydyWWOXTgW/gtRP/pniFbDqEBJeQnLC5azausq4qLjWHr9UmaPn43L6Yp0ae2SMYbjVVWh\nyy0DYVlxeTkn64VkfWJiSHe7GZuQwB3JyaQH5pINdrlwtdGQTEREREREWka4zsgfw+4g+w2AZVmP\nADcD9wErzjzYGPMu8G69m/5gWdZ04BpAAZp0Gr/9jeHdB1fz+6rHYcBAov77LRg7NtJlSRtQ6itl\n1dZVrNi8Al+NjzmZc5h71Vy6xnWNdGntwonaTrJAMFY/LPuyurruuN4xMQxxubg8Pp7bAiFZeiAk\ncyskExERERHptFo8QLMsywmMBZbW3maMMZZl/RVo0lZwlmWNDhyb09L1ibRFXi/k3HuYr794H8/w\nGr4Hv0vMT1aA2x3p0iTCfDU+1uxYw6K/LeJ42XEeueIRcq7JISU+JdKltTlf1l9ueUZYdqJeSJYa\nE0O6y8UlHg/f7NHDDsncboa4XHgUkomIiIiISAPC0YHWA4gCjp5x+1Fg2LkeaFnWIaBn4PFPGmP+\nIwz1ibQpO3bAv9/8IguPPIQrMQbW/omYm26KdFkSYX7jJ3d3LgveXMC+kn3MvHQmCycvJC0pLdKl\nRdTJ6mo7FAvMI6s/uP+Lqqq645KdTtJdLkZ4PGQFQrIhga8ELYcWEREREZFmamtnEVcD8cAEYLll\nWcXGmP881wMee+wxEhMTQ2678847ufPOO8NXpUgLMAZ+seIUnnnf56fm15ye8g+4f/889OgR6dIk\ngowx5BXlkZ2fza6ju8galsXLd7zMqORRkS6t1Xirq0OCsfph2ef1QrKeTidDXC6Gulzc3K1b3eD+\nIS4XXRSSiYiIiIh0WLm5ueTm5obcdvLkybA+p2WMadlvaC/hLAOmG2PW1bv9V0CiMeabTfw+OcBM\nY8yIRu4fA2zfvn07Y8aMufjCRVrRF1/Av2Zt4pEt36ZXzHGifroK5wP3gHbF69Q2HdjEvNfnUXCo\ngEkDJrHsK8vI7Nekle/tzunaTrIzusiKyso4Wi8k6x4dXbe8Mr3e1xCXi65O7TgqIiIiIiK2HTt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GLcZ+O47u3r+HHJj5yyxyn835//jzbbtUl1aZIkSZKkbZwBmiqeiROJp5/O6oUr6cMTrD78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\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+yMzevflnkyYnwrK0tDLnOwNCOBrYiL2uaHYcb8Je05uDVjS2po2oc3E0jXtF025gFBf3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\nrKZXV6ygS/ZsvslbB3Me4+aj69C/09tULFdxj9U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5Oj+fJ2rXpkHhl1z2fEMW5ixkYLOB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\nQJMkSZIkSZJ24P8BcVMCR/lTO1YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb984b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "learning_rates = {'rmsprop': 1e-4, 'adam': 1e-3}\n",
    "for update_rule in ['adam', 'rmsprop']:\n",
    "  print('running with ', update_rule)\n",
    "  model = FullyConnectedNet([100, 100, 100, 100, 100], weight_scale=5e-2)\n",
    "\n",
    "  solver = Solver(model, small_data,\n",
    "                  num_epochs=5, batch_size=100,\n",
    "                  update_rule=update_rule,\n",
    "                  optim_config={\n",
    "                    'learning_rate': learning_rates[update_rule]\n",
    "                  },\n",
    "                  verbose=True)\n",
    "  solvers[update_rule] = solver\n",
    "  solver.train()\n",
    "  print()\n",
    "\n",
    "plt.subplot(3, 1, 1)\n",
    "plt.title('Training loss')\n",
    "plt.xlabel('Iteration')\n",
    "\n",
    "plt.subplot(3, 1, 2)\n",
    "plt.title('Training accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "\n",
    "plt.subplot(3, 1, 3)\n",
    "plt.title('Validation accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "\n",
    "for update_rule, solver in list(solvers.items()):\n",
    "  plt.subplot(3, 1, 1)\n",
    "  plt.plot(solver.loss_history, 'o', label=update_rule)\n",
    "  \n",
    "  plt.subplot(3, 1, 2)\n",
    "  plt.plot(solver.train_acc_history, '-o', label=update_rule)\n",
    "\n",
    "  plt.subplot(3, 1, 3)\n",
    "  plt.plot(solver.val_acc_history, '-o', label=update_rule)\n",
    "  \n",
    "for i in [1, 2, 3]:\n",
    "  plt.subplot(3, 1, i)\n",
    "  plt.legend(loc='upper center', ncol=4)\n",
    "plt.gcf().set_size_inches(15, 15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Train a good model!\n",
    "Train the best fully-connected model that you can on CIFAR-10, storing your best model in the `best_model` variable. We require you to get at least 50% accuracy on the validation set using a fully-connected net.\n",
    "\n",
    "If you are careful it should be possible to get accuracies above 55%, but we don't require it for this part and won't assign extra credit for doing so. Later in the assignment we will ask you to train the best convolutional network that you can on CIFAR-10, and we would prefer that you spend your effort working on convolutional nets rather than fully-connected nets.\n",
    "\n",
    "You might find it useful to complete the `BatchNormalization.ipynb` and `Dropout.ipynb` notebooks before completing this part, since those techniques can help you train powerful models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(Iteration 1 / 2450) loss: 2.292392\n",
      "(Epoch 0 / 5) train acc: 0.108000; val_acc: 0.109000\n",
      "(Epoch 1 / 5) train acc: 0.519000; val_acc: 0.476000\n",
      "(Iteration 501 / 2450) loss: 1.548382\n",
      "(Epoch 2 / 5) train acc: 0.573000; val_acc: 0.492000\n",
      "(Iteration 1001 / 2450) loss: 1.151230\n",
      "(Epoch 3 / 5) train acc: 0.580000; val_acc: 0.506000\n",
      "(Iteration 1501 / 2450) loss: 1.058257\n",
      "(Epoch 4 / 5) train acc: 0.642000; val_acc: 0.553000\n",
      "(Iteration 2001 / 2450) loss: 0.746325\n",
      "(Epoch 5 / 5) train acc: 0.680000; val_acc: 0.548000\n"
     ]
    },
    {
     "data": {
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cdZdbF+1aWEn9+xeuLIubDTN6jKhFi6TDDw+fJ1WWueMmzYaZds2X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\nGXbiiago5G2hkWXTp+vKMh9RH6OU9Y35m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r1G1dWbNH36\nAbryygdUW1tbkfsupQ8++CBlfLGamhqNGjVKb775ZpN1f/KTn+jGG29Mud2pU6eds2ZmcuSRR+qJ\nJ57Qr3/9a5144omSpIaGBv34xz9WbW2tJk+enLL+7373O7399tsaNGiQJOmFF17Q888/r2984xsF\nnScAIF5Dg/T++7l1g/zgg9RtzaR+/ZJVXiNGSBMnxneD3GUXqaqqPOcIlBphGQAAaNVqa2s1f/5c\nzZ+vZg+435L7LpU999xTBx98sMaPH6/evXvrr3/9q+6//35dcMEFKet17txZjz32mE4//fSdA+0/\n+uijmjNnTpPx0uKcddZZuvXWW3X66afrb3/7m4YPH6777rtPzz33nObPn58yE6bkxyw78MAD9dWv\nflVbtmzR/Pnz1a9fP33zm98s6vkDQHNU6u9656R163LrBrlmjQ/Mwnr2TA289t47vhtkv36MAwZI\nhGUAAKANKeUHnJb88JTuWHHLzSxl+YUXXqhFixbpiSee0NatWzVs2DBdffXVuvjii1O269ixox57\n7DGdc845uuSSS1RbW6u5c+fqsssuy7j/QJcuXfTMM8/o29/+tu68806tX79edXV1uv3223Xqqac2\nWf+0005TVVWVbrzxRr333nuaMGGCfvzjH2vAgAE5PSYAUCobNmzQnDnX6aGHntX27d1UXb1R06Yd\noKuuurjkVcSbNmUOv8LLt25N3bZr19Sga+LEpuFXEIh16VLS0wDaHAsPCFspzGycpMWLFy/WuEJH\n5QUAAK3akiVLNH78ePH3QPHNnj1bDzzwgNavX1/yY61atUojRozQddddV1CXS14HAEppw4YNmjhx\nhurrv6HGxqlKjk/5uMaOnafnnsu/2/327dJ772UPv1avljZsSN22Y8dk4BUXfIUDsNpa320SaA+C\nvwckjXfOLSn18agsAwAAAAC0S3PmXJcIysIzH5saGw9Xfb3TpZder/nz56qxsek4YOmqwd5/v+lx\n+vZNBl3DhkkTJjQdA2zgQKl3b8YBAyoBYRkAAAAAoF166KFn1dg4N/a+xsbDdcst83T//T4Yi44D\n1qNHarXXJz4RXw3Wr59UXV36cwFQPIRlAAAA7VBLj8FWiQNmA2g/GhulN9+Uli5Nfv3nP05vvNFN\nvutlHFN1dY3OPNNp112tSTfIrl1b8gwAtCTCMgAAgHbmtttu02233dYixxo2bJgaouUYAFAi69f7\nIGzZstRgbNkyafNmv051tTRqlFRXZ+refaPWrXOKD8yc+vXbqO99j7AfaG8IywAAAAAArcaOHdLK\nlalhWPC1enVyvV13lerqpM98Rpo1y/9cV+fHDOuY+CR8wQUHaMGCxyNjlnlVVY9p+vQDW+akAFQU\nwjIAAAAAQMVZu7ZpGLZsmbR8uZ9xUpJqaqQxY/zXQQclA7ExY/yYYtlcddXFeuqpGaqvd4nALJgN\n8zGNHXuDrrzygVKeIoAKRVgGAAAAACiLrVt9+BXtNrl0qfTBB34dM2noUB+CHXqodO65yVBs8ODm\nzR5ZW1ur5557QJdeer0WLZqn7dtrVF29SdOnH6Arr3xAtbW1xTlRAK0KYRkAAAAAoGSck955J77b\n5MqVfvB9SerZMxmCHXVUskJs9OjSDqZfW1ur+fPnav58yTnHhCQACMsAAEBlq6+vL3cTUEY8/0Dr\nsXFjaoVY8POyZdKGDX6dDh2kkSN9EHbssclwrK5O6t/fV5GVE0EZAImwDAAAVKi+ffuqpqZGM2fO\nLHdTUGY1NTXq27dvuZsBQFJDg/TGG/FVYm++mVyvXz8fgO23n3TiiclAbORIPxslAFQywjIAAFCR\nhg4dqvr6eq1du7bcTUGZ9e3bV0OHDi13M4B25aOP4gOxV17x44xJUufOvotkXZ102mm+y2QQiu2y\nS3nbDwDNQVgGAAAq1tChQwlJAKBEtm+XXn21abfJpUul995Lrjd4sA/AJk2SzjwzGYgNHeq7VQJA\nW0NYBgAAAABtlHPSmjXxVWKvvirt2OHX6949WRk2ZUoyEBs92t8HAO0JYRkAAAAAtHJbtvguktFA\nbNky36VSkqqqpOHDfQh25JGp3SYHDSr/4PoAUCkIywAAAACgFXDOD6If7TK5dKm0apW/X/LjhdXV\nSWPHSscckwzEdt9d6tKlvOcAAK0BYRkAAAAAVJANG5qGYUFAtmmTX6e62odfdXXSCSckA7G6OqlP\nH6rEAKA5CMsAAAAAoIU1NEgrV8YHYm+/nVxv4EAfgH3609LMmclAbMQIqSOf5gCgJPj1CgAAAAAl\n8v778d0mly+Xtm3z63Tt6gfSr6uTDjwwGYiNGSP17Fne9gNAe0RYBgAAAADNsG2btGJF/IyT77+f\nXG/oUB+Cfe5z0le/mgzEhgzxg+8DACoDYRkAAAAAZOGctHp1fLfJ117z3SolqUePZAh2+OHJKrHR\no6WamvKeAwAgN4RlAAAAAJCwaZP0yivxodj69X6dDh38mGF1ddL06amD6w8YwOD6ANDaFRSWmdm5\nki6WNFDSPyWd75z7a4b1O0m6XNKXEtu8LekK59zthRwfAAAAAArV2Ci98UZ8t8k33kiu17evD8D2\n2Uf64heTFWO77y516lS+9gMASivvsMzMTpR0vaSzJL0g6SJJj5vZGOfc2jSb3Sepn6TZklZI2lUS\nvfIBAAAAlMy6dU2rw5Yu9ZVjmzf7dTp18l0kx4yRvvSl1Cqx3r3L234AQHkUUll2kaRbnXN3SpKZ\nnSPpKElflvSj6MpmdrikSZJGOuc+Six+vbDmAgAAAEDSjh1+zLC4KrF3302uN2iQD8A++1lp9uxk\nIDZsmO9WCQBAIK+wzMyqJY2XdHWwzDnnzOxJSRPTbDZN0t8kfcvMTpW0UdIiSZc557YU1GoAAAAA\n7YZz0tq18YHYihU+MJOkbt18hVhdnXTIIcluk2PGSLW15T0HAEDrkW9lWV9JHSS9G1n+rqS6NNuM\nlK8s2yLpmMQ+fiqpt6Qz8jw+AAAAgDZqyxZp+fKm3SaXLpU+/NCvY+arwerqpKlTU7tNDh7M4PoA\ngOZridkwqyQ1SjrFOfexJJnZNyTdZ2Zfc85tTbfhRRddpJ49e6YsO/nkk3XyySeXsr0AAAAASsQ5\n6e2346vEVq3yg+9LUq9eyRBs2rTkz6NGSV26lPccAACls3DhQi1cuDBl2bp161q0Deacy31l3w1z\nk6QZzrlFoeW3S+rpnDs2ZpvbJX3WOTcmtGwPSS9JGuOcWxGzzThJixcvXqxx48blfjYAAAAAKsLH\nH6dWhoWrxTZu9Ot07OhnlgyCsKALZV2d1K8fVWIAAG/JkiUaP368JI13zi0p9fHyqixzzm03s8WS\npsiPOyYzs8Ttm9Js9qyk482sxjm3KbGsTr7a7M2CWg0AAACg7BoafDVYtMvk0qXSW28l1+vf3wdg\n48dLp5ySDMRGjJCqq8vXfgAA4hTSDXOepNsTodkL8rNj1ki6XZLM7AeSBjnnZiXWv0fSpZJuM7O5\nkvrJz5r5i0xdMAEAAABUhg8/jO82uXy5tDXxF32XLtLo0T4EO/301GqxXr3K2nwAAPKSd1jmnPuN\nmfWVdIWkAZL+IWmqc25NYpWBkoaE1t9oZp+X9GNJf5X0vqRfS7qsmW0HAAAAUCTbt/uZJeO6Ta5Z\nk1xvyBAfgk2eLJ11VjIUGzpUqqoqX/sBACiWggb4d87dLOnmNPfNjlm2TNLUQo4FAAAAoDick959\nN34ssVdf9d0qJal792QIdthhyZ9Hj5a6dSvvOQAAUGotMRsmAAAAgBa0ebP0yivxVWLBhGJVVX7M\nsLo66eijk4FYXZ00cCCD6wMA2i/CMgAAAKCFOOdkRUqhGhulN99MDcKCn19/3VeRSVKfPj4A+8Qn\npOOOSwZiu+8ude5clKYAANCmEJYBAAAAJbRhwwbNmXOdHnroWW3f3k3V1Rs1bdoBuuqqi1VbW5t1\n+/Xr47tNLlvmK8gkP6PkqFE+BDvppNQqsT59SnyCAAC0MYRlAAAAQIls2LBBEyfOUH39N9TYOFeS\nSXJasOBxPfXUDD333AOqra3Vjh3SypXxM06uXp3c3667+gDsM5+RZs1KzjY5fLjUkb/sAQAoCt5S\nAQAAgBKZM+e6RFB2eGipqbHxcL38stN++12vzp3navlyPxulJNXU+ABszBjpoIOSFWJjxkg9epTl\nNAAAaFcIywAAaGOKOSYSUGrO+bG3tm+XduzwX8HPuS4rZJuWOt769c/Kublpzv1wvf32PH3lK9K5\n5yZDscGD/eD7AACgPAjLAABoA5o7JhIqj3NSQ0NlBD6lPl4pdeyY/KquTv2e7ue4Zd265bZeeFnH\njk5XXtlN69alC69NffrUaP58Am4AACoJYRkAAK1crmMitRXOlS8EasmAqaGhtI9jroFPtoCpa9fm\n76eQ8CqXZR06SOXNoEwLFmzUunVO/rqMcqqu3khQBgBAhSEsAwCglcs0JlJ9vdOFF16vyy6bW5EV\nRYUsa2ws3WNZVVWcoKZzZ1+JVKoQqLkBU1VVuUOk9mPatAO0YMHjkevTq6p6TNOnH1iGVgEAgEwI\nywAAaEWck9askV59Nfl1223PJirKmmpsPFy33TZPt93WvON26FCccKempnxVRrnsm3GiUGxXXXWx\nnnpqhurrXSIw85WfVVWPaezYG3TllQ+Uu4kAACCCsAwAgAqzebO0cmVqIBb+2rQpuW6fPk5bt3ZT\nfBcvKRgT6de/dqqutoLDJKqQgMLU1tbquece0KWXXq9Fi+Zp+/YaVVdv0vTpB+jKK9tWF2kAANoK\nwjIAAFpYY6O0enV8EPbaa9LbbyfX7dRJGjFCGjlSmjxZmj3b/zxihP/q0cM0YsRGrVyZfkyk2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siIhHImLLNh63bUQsiohZHbmuVC4uuQSOOw7GjoWzz7YokyRJkiSpWrS7LIuI/YGJwDjgq8AT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\neuAXVfWxdj80Hy6uqaovdxpO0ouS7AXeX1Wrus4iaX/tl0xPA2dV1dqu80j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      "text/plain": [
       "<matplotlib.figure.Figure at 0x49109e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "best_model = None\n",
    "################################################################################\n",
    "# TODO: Train the best FullyConnectedNet that you can on CIFAR-10. You might   #\n",
    "# batch normalization and dropout useful. Store your best model in the         #\n",
    "# best_model variable.                                                         #\n",
    "################################################################################\n",
    "weight_scale = 2e-2\n",
    "learning_rate = 1e-4\n",
    "update_rule='rmsprop'\n",
    "model = FullyConnectedNet([600, 500, 400, 300, 200], weight_scale=weight_scale)\n",
    "\n",
    "solver = Solver(model, data,\n",
    "                print_every=500, num_epochs=5, batch_size=100,\n",
    "                update_rule='rmsprop',\n",
    "                optim_config={\n",
    "                'learning_rate': learning_rate\n",
    "                },\n",
    "                lr_decay=0.9,\n",
    "                verbose=True)\n",
    "solver.train()\n",
    "\n",
    "plt.subplot(3, 1, 1)\n",
    "plt.title('Training loss')\n",
    "plt.xlabel('Iteration')\n",
    "\n",
    "plt.subplot(3, 1, 2)\n",
    "plt.title('Training accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "\n",
    "plt.subplot(3, 1, 3)\n",
    "plt.title('Validation accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "\n",
    "plt.subplot(3, 1, 1)\n",
    "plt.plot(solver.loss_history, label=update_rule)\n",
    "  \n",
    "plt.subplot(3, 1, 2)\n",
    "plt.plot(solver.train_acc_history, '-o', label=update_rule)\n",
    "\n",
    "plt.subplot(3, 1, 3)\n",
    "plt.plot(solver.val_acc_history, '-o', label=update_rule)\n",
    "  \n",
    "for i in [1, 2, 3]:\n",
    "  plt.subplot(3, 1, i)\n",
    "  plt.legend(loc='upper center', ncol=4)\n",
    "plt.gcf().set_size_inches(15, 15)\n",
    "plt.show()\n",
    "\n",
    "best_model = model\n",
    "\n",
    "################################################################################\n",
    "#                              END OF YOUR CODE                                #\n",
    "################################################################################"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "# Test you model\n",
    "Run your best model on the validation and test sets. You should achieve above 50% accuracy on the validation set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation set accuracy:  0.553\n",
      "Test set accuracy:  0.526\n"
     ]
    }
   ],
   "source": [
    "y_test_pred = np.argmax(best_model.loss(data['X_test']), axis=1)\n",
    "y_val_pred = np.argmax(best_model.loss(data['X_val']), axis=1)\n",
    "print('Validation set accuracy: ', (y_val_pred == data['y_val']).mean())\n",
    "print('Test set accuracy: ', (y_test_pred == data['y_test']).mean())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
